{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4b4bd750",
   "metadata": {},
   "source": [
    "# 3. In-Built Data Structures"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c728db71",
   "metadata": {},
   "source": [
    "Agenda\n",
    "\n",
    "- string\n",
    "    - Representation\n",
    "    - Slicing\n",
    "    - Methods\n",
    "\n",
    "- list\n",
    "    - Representation\n",
    "    - Methods\n",
    "    - Comprehension\n",
    "    - 2D Lists\n",
    "    \n",
    "- tuple\n",
    "    - Representation\n",
    "    - Lists VS Tuples\n",
    "    - Unpacking\n",
    "    - Operations\n",
    "\n",
    "- set\n",
    "    - Representation\n",
    "    - Operations\n",
    "    \n",
    "- dictionary\n",
    "    - Representation\n",
    "    - Accessing\n",
    "    - Deleting Elements\n",
    "    - Functions\n",
    "    - Nested Dictionaries\n",
    "    - Comprehension\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fd23f31",
   "metadata": {},
   "source": [
    "## 3.1 string"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "09bafb55",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12ffe4fb",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Hello World!\"\n",
    "\n",
    "print(type(s))  # Hello World!\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41ec508f",
   "metadata": {},
   "source": [
    "### Length"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "418dc07a",
   "metadata": {},
   "source": [
    "get the len of a string"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57aa0c86",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Hello World!\"\n",
    " \n",
    "print(len(s))  # 12\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36a59688",
   "metadata": {},
   "source": [
    "### Indexing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82de9e9c",
   "metadata": {},
   "source": [
    "accessing one character based on the position.\n",
    "\n",
    "indexing starts with 0.\n",
    "\n",
    "indexing number can not be bigger than the len of string."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddbdd0bf",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Hello World!\"\n",
    "\n",
    "print(s[0])  # H\n",
    "\n",
    "# get the len of a string\n",
    "print(len(s))  # 12\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b36866f",
   "metadata": {},
   "source": [
    "- Negative Indexing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08c6bf30",
   "metadata": {},
   "source": [
    "```python\n",
    "print(s[-1])\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "832bba75",
   "metadata": {},
   "source": [
    "### Slicing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28c1b14c",
   "metadata": {},
   "source": [
    "extracting multiple characters from a string(sub string)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b999b157",
   "metadata": {},
   "source": [
    "- Syntax: str[start_index : end_index]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b28fd6d",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Hello World!\"\n",
    "\n",
    "print(s)  # Hello World!\n",
    "print(s[:])  # Hello World!\n",
    "\n",
    "print(s[6:11])  # World\n",
    "print(s[6:])  # World!\n",
    "\n",
    "print(s[6:-1])  # World\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c63633a",
   "metadata": {},
   "source": [
    "- Syntax: `str[start_index : end_index : step_size]`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30b17272",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Go Go Go!\"\n",
    "\n",
    "print(s[1:9:3])  # ooo\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "636a260a",
   "metadata": {},
   "source": [
    "- Reverse a string"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7aaa90e",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Hello World!\"\n",
    "\n",
    "print(s[::-1])  # !dlroW olleH\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e516c4da",
   "metadata": {},
   "source": [
    "### Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ac2e220",
   "metadata": {},
   "source": [
    "show all the available methods in str class.\n",
    "\n",
    "```python\n",
    "methods = [x for x in dir(str) if not x.startswith(\"__\")]\n",
    "print(methods)\n",
    "\n",
    ">>>\n",
    "['capitalize', 'casefold', 'center', 'count', 'encode', 'endswith', 'expandtabs', 'find', 'format', 'format_map', 'index', 'isalnum', 'isalpha', 'isascii', 'isdecimal', 'isdigit', 'isidentifier', 'islower', 'isnumeric', 'isprintable', 'isspace', 'istitle', 'isupper', 'join', 'ljust', 'lower', 'lstrip', 'maketrans', 'partition', 'replace', 'rfind', 'rindex', 'rjust', 'rpartition', 'rsplit', 'rstrip', 'split', 'splitlines', 'startswith', 'strip', 'swapcase', 'title', 'translate', 'upper', 'zfill']\n",
    "​\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46226faf",
   "metadata": {},
   "source": [
    "```python\n",
    "s = \"Hello World!\"\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a985ca73",
   "metadata": {},
   "source": [
    "- `lower()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44f2e647",
   "metadata": {},
   "source": [
    "converts everythin in lowercase."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ef05b6b",
   "metadata": {},
   "source": [
    "- `upper()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42bd6cc2",
   "metadata": {},
   "source": [
    "- `title()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8233d650",
   "metadata": {},
   "source": [
    "- `find()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "426b8608",
   "metadata": {},
   "source": [
    "```python\n",
    "s.find('ll')  # 2\n",
    "s.find(\"he\")  # -1\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "077a541b",
   "metadata": {},
   "source": [
    "- `split()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f32a7897",
   "metadata": {},
   "source": [
    "```python\n",
    "s.split(\" \")  # ['Hello', 'World!']\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9f3fd0a",
   "metadata": {},
   "source": [
    "- `count()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abdfc3b2",
   "metadata": {},
   "source": [
    "```python\n",
    "s.count(\"l\") # 3\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67cf8636",
   "metadata": {},
   "source": [
    "- `replace()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a348e45b",
   "metadata": {},
   "source": [
    "```python\n",
    "s.replace(\"World\", \"Python\")  # 'Hello Python!'\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "262fc804",
   "metadata": {},
   "source": [
    "### Operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8273e66",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "48d85a0f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "abcxyz\n"
     ]
    }
   ],
   "source": [
    "s1 = \"abc\"\n",
    "s2 = \"xyz\"\n",
    "\n",
    "print(s1 + s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd213987",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Bad way\n",
    "print( s1 + 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bee6628",
   "metadata": {},
   "source": [
    "- repeating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e89c68d",
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 * 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a906dee",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "763e7a4b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6c65c7c5",
   "metadata": {},
   "source": [
    "## 3.2 list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da627a17",
   "metadata": {},
   "source": [
    "- ordered/sequence collection of elements\n",
    "- indexable\n",
    "- mutable\n",
    "- can store heterogenous elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dffe86ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "### creating empty list\n",
    "\n",
    "li1 = list()\n",
    "li2 = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "7d9fc2d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "5\n",
      "[2, 3]\n",
      "[4]\n",
      "[2, 4]\n",
      "[5, 4, 3, 2, 1]\n"
     ]
    }
   ],
   "source": [
    "### indexing\n",
    "\n",
    "li = [1, 2, 3, 4, 5]\n",
    "print(li[1])\n",
    "print(li[-1])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0ee58ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "### slicing\n",
    "\n",
    "print(li[1:3])\n",
    "print(li[3:-1])\n",
    "\n",
    "print(li[1:5:2])\n",
    "\n",
    "print(li[::-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e930983",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(len(li))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1b9ab6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "### mutable\n",
    "\n",
    "changing element\n",
    "\n",
    "li[0] = 0\n",
    "print(li)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be9d7153",
   "metadata": {},
   "source": [
    "### methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b82d36a",
   "metadata": {},
   "source": [
    "- `append()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "7cda0dbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 100]\n"
     ]
    }
   ],
   "source": [
    "li = [1, 2, 3]\n",
    "\n",
    "li.append(100)\n",
    "print(li)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20d7d987",
   "metadata": {},
   "source": [
    "- `insert()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "0859c750",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 99, 2, 3, 100]\n"
     ]
    }
   ],
   "source": [
    "li.insert(1, 99)\n",
    "print(li)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72322d2f",
   "metadata": {},
   "source": [
    "- `pop()`\n",
    "\n",
    "Remove and return item at index (default last)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "268fc800",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 [1, 99, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "x = li.pop()\n",
    "print(x, li)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "44da86a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 [1, 2, 100]\n"
     ]
    }
   ],
   "source": [
    "y = li.pop(2)\n",
    "print(y, li)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "815b2fe4",
   "metadata": {},
   "source": [
    "- `li.remove()`\n",
    "\n",
    "Remove first occurrence of value."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b5a2db3",
   "metadata": {},
   "source": [
    "- `reverse()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85a0a021",
   "metadata": {},
   "source": [
    "- `sort()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "688a8a74",
   "metadata": {},
   "source": [
    "- in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "c4f89976",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n"
     ]
    }
   ],
   "source": [
    "print(1000 in li)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "702a0fa2",
   "metadata": {},
   "source": [
    "- `extend()`\n",
    "\n",
    "Extend list by appending elements from the iterable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "afc5e42d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, [88, 99, 100]]\n",
      "[1, 2, 3, [88, 99, 100], 88, 99, 100]\n"
     ]
    }
   ],
   "source": [
    "li_1 = [1, 2, 3]\n",
    "li_2 = [88, 99, 100]\n",
    "\n",
    "li_1.append(li_2)\n",
    "print(li_1)\n",
    "\n",
    "li_1.extend(li_2)\n",
    "print(li_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "933c70d0",
   "metadata": {},
   "source": [
    " extend using +"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "5b5bb82b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5, 6]\n"
     ]
    }
   ],
   "source": [
    "li_3 = [1, 2, 3] + [4, 5, 6]\n",
    "print(li_3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb665cd0",
   "metadata": {},
   "source": [
    "- `join()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "5380d6a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello_World_!\n"
     ]
    }
   ],
   "source": [
    "li = [\"Hello\", \"World\", \"!\"]\n",
    "print(\"_\".join(li))  # Hello_World_!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f93306d",
   "metadata": {},
   "source": [
    "### Heterogenous List`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "22792132",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "li_mixed = [1, True, 3.14, [1,2,3], \"Python\"] \n",
    "\n",
    "print(type(li_mixed))  # <class 'list'>\n",
    "print(len(li_mixed))  # 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "71e9448e",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<' not supported between instances of 'list' and 'float'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mC:\\Users\\ADMINI~1\\AppData\\Local\\Temp/ipykernel_5532/1279493100.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mli_mixed\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msort\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: '<' not supported between instances of 'list' and 'float'"
     ]
    }
   ],
   "source": [
    "print(li_mixed.sort())  # TypeError: '<' not supported between instances of 'list' and 'float'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "ee15211f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, True, 3.14, [1, 2, 3], 'Python']\n"
     ]
    }
   ],
   "source": [
    "li_mixed.reverse()\n",
    "print(li_mixed)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04923e82",
   "metadata": {},
   "source": [
    "### list comprehension"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da7699b6",
   "metadata": {},
   "source": [
    "To creating a new list of squares of each element."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d095bae",
   "metadata": {},
   "source": [
    "```python\n",
    "# normal solution\n",
    "li_1 = []\n",
    "\n",
    "for ele in range(1, 11):\n",
    "    li_1.append(ele ** 2)\n",
    "print(li_1)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e8a7bbd",
   "metadata": {},
   "source": [
    "```python\n",
    "# list conprehension solution\n",
    "\n",
    "li_2 = [ele ** 2 for ele in range(1, 11)]\n",
    "print(li_2)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18fadbe4",
   "metadata": {},
   "outputs": [],
   "source": [
    "### 2D list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "b9ad18a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1, 2, 3], [4, 5, 6], ['x', 'y', 'z']]\n",
      "['x', 'y', 'z']\n",
      "6\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "x\n",
      "y\n",
      "z\n"
     ]
    }
   ],
   "source": [
    "li_2d = [[1,2,3], [4,5,6], [\"x\",\"y\",\"z\"]]\n",
    "\n",
    "print(li_2d)  # [[1, 2, 3], [4, 5, 6], ['x', 'y', 'z']]\n",
    "print(li_2d[2])  # ['x', 'y', 'z']\n",
    "print(li_2d[1][2])  # 6\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "36cbe27e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3 4 5 6 x y z "
     ]
    }
   ],
   "source": [
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        print(li_2d[i][j], end=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e41d8405",
   "metadata": {},
   "outputs": [],
   "source": [
    "### More on list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f17d082",
   "metadata": {},
   "source": [
    "- repeating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "66c54865",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "li = [1] * 10\n",
    "print(li)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "cb54af83",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]\n"
     ]
    }
   ],
   "source": [
    "li_2d = [ [1]*5 ] * 5\n",
    "print(li_2d)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e5ca16d",
   "metadata": {},
   "source": [
    "- `copy()`\n",
    "\n",
    "List having multiple references"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "cd5655c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4]\n",
      "[1, 2, 3, 4]\n"
     ]
    }
   ],
   "source": [
    "a = [1, 2, 3]\n",
    "b = a\n",
    "b.append(4)g\n",
    "\n",
    "print(b)  # [1, 2, 3, 4]\n",
    "print(a)  # [1, 2, 3, 4]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "155272e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4]\n",
      "[1, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "a = [1, 2, 3]\n",
    "b = a.copy()\n",
    "b.append(4)\n",
    "\n",
    "print(b)  # [1, 2, 3, 4]\n",
    "print(a)  # [1, 2, 3]\n"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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wG5uKKQQKgUKgECgECoFCoBAoBDZ4BMpg2OC7QAFQCBQChUAhUAgUAoVAIVAIzEagDIbZ2FRMIVAIFAKFQCFQCBQChUAhsMEjUAbDOt4F/vOf/6zjNajiFwKFQCFQCBQChUAhUAiszQiUwbA2t84CZYux4JjzBZIsmm8hOas7PnX697//vUqyWiw+0zJbVWWYJntW2MqUd5bMaeHBeVrc2hK2slik/daFuq4uzFcWw9VVruWRqw5py+VJtyZ4p5VzbWuDhcojfiGeNYHtQnmuqXIHK22f8/nK+q9//Wu+6FUat6YwSSWm3Q+Jq+O6g0AZDOtOW20wJe0H21Ux0I3lAXJVyN1gGqQqerYjMO6ffR8+2wuzFmQ4xmMtKNKCRRi32fh6QQHFsMIIrAms+zz783El5osb89Z1IbA2IVAGw9rUGitZFjMWP/nJT4bf/OY3C0qaNWjNCl9Q4BSG5ZE1H28fN+t8SvZzgv74xz8Ov/3tb+eE9bL6iHH47373u+HPf/5zz7Lc52OZYwGz4ucLFzdf/DiP8XWftj+fxtfHO89vzJvrnj9h/THxOfZx086Xlw9/fr28WTNdY/mnnnrqVGynyezlO+9lzTofpxlfJ93SpUuHM844Yxw99TpppkYuInBl0y8ii7OFZVY9ZoWvaKEWkpf4v//978M///nPFcomMlYo8WpM1Jdr1j21mOx7ObPOeznz8fTl6PmkX+i6z2NFzvu8F3pW9LzTyrY8+Y/rNU47X/x8cWM5K1POvr7JM8fI7a+T97SwxNVxzSBQBsOawX2V5NrfUI961KOGS1/60sN5z3ve4cIXvvBwwxvecDj22GOHLHuedNJJw/Wud7324Eo6N3LOxwUSnrSJ68OkFe9B6NcPCvjH19IK83PuN6aHPOQhw5Of/OQWvPvuuw8vf/nLJ3zJS+Tf/va3SVLhS5YsmVw7iewcKfxXu9rVhq985SvDgx70oOERj3jEHH4X5PRlpjB+/OMfb3xf/epXhytd6UqDsDH94x//aEGp1zh+fJ18Uh9lnKZMvPa1rx1ucYtbzCnTWNa0a/L6erhOntP4n/vc5w76Dkq61GlcrtNPP304+uij54j5y1/+Mue6lyPftIEjxSl5nCXRKOCd73zncPnLX76FJk2OySPyr3Wtaw2HHHLISMJ/6yPf17/+9cOee+45Jz7lEphz9Sbz+c9//vC0pz2t8ctTWM/n/E9/+lO7v1ImR3gFu1yP07meRsljHPed73xnuNGNbjQOnnl93eted3jwgx88/P73v5/UK8yPf/zjhxvf+Ma5bO3hos972r2MR72CU+osPGHOxxS5f/3rX8dRk2t9IkRWZDsfyzYZcpOb3GRSbul6HuNAlDVy/JTBMe3S84cnclwn3vm4bPjG+CRN8El6vOg+97nPcIlLXGLYa6+92rWxS5nw5dgiur+UNfhlvEte4zyUM7ydmEmdycu9vOuuu04d/6TD08t+6lOfOtzlLnfpRbbzlM94+MlPfvIs8QLCM45MeI9twvAac7///e+3ZCmzC+VS/zEZj4xLoZvd7GbDoYcemsvJUfrI6OsYTJUh4f35REB3Ej5BfRnf9ra3DVe+8pWH61//+sMvfvGLLsV/x6LPfvazw69//esW7v684x3vOHi2IOWASS9beOT3dcfjl7InTY7SoVwry61udavhi1/84pzw8EzrO+mn4WkJl/1N67N9GeWZfB/5yEcOe++9d0v6hCc8YXj3u9/dzhPfLkZ/nid0FeMrStnmSzMSUZerEYEyGFYjuGeHaDcSA+Ec5zjH8MpXvrLNolOMKZvCMiAdccQR7bovk7QGndyUfZzzfuDMQDEepJIm4bnuj3k44DG4yHfaAEAZMLCh+93vfsOTnvSkdj6Nt0Us+/vhD384nPOc5xxOPvnkBM05qsMb3vCGNjiLYDjc/OY3n/CID/UP5te85jUTvJT7bne72/CSl7wkrGc5KmNkRQ4maceEL4PsLCwoGOc+97mnppcmcnOURx+ePMXPygPPwx72sOEGN7hB2Jtc/KH+/IMf/OBwrnOdK1FzjvrHrH6U/FNnCYW57sN6gS9+8Ysb/n39Et+XSZ76eR5Mke2YPrvHHnu0/tTHOQ+RhzcPSfI+97nPJXpyxKPt8H/pS18aznOe8wzf/e53W7ywvly5Vv6UI/Fpk/SXhBPUn+f6mte8ZjNicu04i0477bSGx2677dZYkgfjW70+/elPnyXpOM+eIfXtw9QHpW1cO9eWyS9h+Hr5/bm4MSU+xz7+W9/6VqsDZSJ5O/pRxC5zmcvMVIoiZyzX9ViWsJ7Ped9Px/XvZfTpKD4w/8hHPjKzr/f8KWN/THyO4pSlv+75c97HO0+ZjauMSpR6i+/Pw8tY2GKLLRpv5Dnm/NWvfvWw8cYbT+ITLsB5ZObYYxielrj7u+AFLzjssMMOLSTpuuh2mvK52GSTTQaTK6GNNtqoPQdz7ZhySZfzxKe/5nraMXVRHuf5jXk9WxiI4qfJ3WqrrYb3vOc9LRkj52IXu9jw5S9/eY6Y3EPJq49M+ZN/fwyffKUNRs6XLl3axu0lS5aErR2lFx/KubR9Xs7HbZc0/VH6lEm45/lDH/rQxuK5Tj8xxuLp8UlZMX7ve98bNt100+Yp0RLW31qFQBkMa1VzLH9h9t9//8lDaZx6m222aXEJz4P2G9/4xvCrX/0qwe3ogSscuYG573z+858fPvWpTw1m6EOnnHLK8KMf/Wj4+c9/3maDTjzxxLO4+oQ3R0r9UUcdNRx33HFNwU/4+MjI2XbbbVuwgSWGhsGFEXT88ccP8vvZz37WeMzSfPjDH251fMtb3tIGxrFM1xe60IUGCii6ylWu0oypdrHszwzuMcccM3ziE5+YYPKHP/xhMBvrYf+FL3yhDZZmrVz3g6KBz0CagRYuBmW/b37zm5NBEZY//vGPB3LNyMmrnxVTFi5TFAwzbLB9znOeM9NgCD/lT/top95IgZU8ld0q09JlDwykvGPS1kkLV+VWFmWENQUU4TnggAOacUZZjpuMNiLDzJD+kwdGMGGwmhlGZn+V2aygumZ1guyvfe1rjYcCrvxIHnlQcbMLPjDs+6R22W+//VqdGcYwUQdlUQ4GwwMe8IAm07Uya/f3v//9AyW0p9vd7nbDrW9960mQdtPv+plPM+bveMc7Wn84/PDD5/RpfV35YJdZMsJ++ctftv5lVlb5tEs/C6ms+oS0+ho5qbuZOQ9f/X0+SvtapYOJfoHM2DKq73CHO7RruJvtVCd9BB5Ji/enP/1p40v+2iT9IO3aGJb9Zcyg+LiP0o6Jd6QEwFD7RWby066MM3hkBQ9P4s2K6ovaSznUI6sIZKfvkX3Ri160YZf+Jj7yP/rRj04mT8hWj+SBL/3XubooL2xQz6dfmZxQV2MhIss9+4Mf/KDdJ9LhedGLXtQUNfXS/kg+6mss1D59P4a9cVkY+dobvvoRXI2hsETy/tjHPtZkZJxsEd0fWenfn/nMZ1oZ5a8OaUfjBIz1BfjiTzvc8573bKvWRLpv/TJu6Q9W4fQz/SUz51327TmxdNnY434hP2nVE77kZSzHo97nO9/5hu22267VPX1FXTNu6gdInaVlsDz96U9vuHlOqFtP6ude9Jz49re/3Ue1PgUHY5T+ASMkTL+aRvDXNieccEIbz/EoizZlABgXcv8kvbrJg/GlTwQvK0+wF6dtc79Klz5nPFZ3+cFD2RIX+Tlqb2Vbsuz5o88oU/pGxmv9MP1WOvL0M2N6eGGoD2uj/l7SlsYlzzH3pHtWnsoTQ8V5ytcbDMqT9jTeuz+U8wMf+MBkbCFLO2nTI488stUhslLHOq5ZBMpgWLP4r3DuuZE222yz4Za3vOVETgYVAQbpV73qVS3OgGRwR3e6052Ge93rXhNFUVjvqmMwMLiZrZHGjHwGDjMFV7ziFYdrX/vawwUucIEW/7Bls9T9jAF5oRe84AVtxsCDgKwtt9xysuQcnhwtJzNy0H3ve9/BkjjyYORqZcadjMtd7nLt4WzW1Iy3MD8rCcElRwqDuCgyZoEMZIiRIc6MhqM6Gwzf/OY3t2th8n3pS1/a+C91qUu1gdIF+QbbkEEdrzT5mZFHlqpvetObtl/iYLh02QCM5Hn729++pTNr7cGjjMrV59GYl/15UF796ldv/GkDLjdRBMggDzbBDIahYOPaDFD6z7Oe9axWB0vlKadyy89sojDy9AuGak8eRNrl4IMPbsEpN2PtoIMOasqCVRoyzAo6ZibRg9o1NzTHS17yksOHPvShdk4YxToG3EUucpEWfpvb3GaCnzTqcNnLXrbN+rtWB23vwQ+bnXbaaVJcfR9PsFG3kHDlQJSIq171qo1XuNnP973vfa0vuY4M9xNiPFACEseVKA9JriBmdmGUPuv861//ekvLiDBDnrSOHp4Ij2t9bCGSH+Xg/Oc/f3ONwK/u0gvXLu6tPh/3WRTaK1zhCm1s6PPRx+JS04d7wMuHwtbLSx/Ay1Cn5Ceem0KI8md1i4IgXrvDATEKuMslnaMxamww4KVoiSfHj8KJKIgmIHoZe5/pIiG+v4cpQtrjsY997Bz+3pXNfXDXu951Ei+vtBGj1D3Lva/Pz7kyZ3XyMY95zJz4nXfeWVEacReDs/FWOkqcPsrYDUaMohe+8IWDdgquz3zmMyNizlE/1h89A8h72cteNjzwgQ+cM2Hy6Ec/elIe4436ubfQPe5xjzYeGAOMKWRkBdjkgWtjgXHvFa94xZy8XcDesyFtwEh905veNHluSG88pgxTqjOmyUsZGDfw9czAm/vGeGpSgcuicL/tt9++5a8OWXFgbCXv8GXiCLP7k6tM4hzzzGnCRn/vete75vByUzWGa6fI0E7Gnp4YBOqU9jJeeF56nmiPpHXUtiHKtLCMU9JFqQ9Pjoyw4CSNektnEkvfpicwqt/73ve2fBm4yD1gkkW/Ms4yiPTjlMkzUfsgfUN7kZ1nHTdnRhkiq3+2kJMVBpMwnteIi6h+EzysoLq39OPUVf6en728lrj+1igCZTCsUfhXPnMDkYEdzXdzWRZ3E1IY3IjOM6NhQHMd/3Tn/KANNAZ5io4HHTIIGCwoWacsm/kxE4DfID6NxJlVMSPl5zqK4pifwZAHkgfA//3f/7U6UTrlT6mhBFjaNXga9MxykEkpzQwspSlYGJwMzLk2yFvJQJRPy6QUKTM55FC00S677NKuKbOZMVK+e9/73i2evCjFFFNlNPgrn4F3xx13bA91zG9961ubrGc/+9ktniFH+czDyzI2Jfqwww5rs3xRziljyaNleuafh7CB3CwNQ04dlN01Bdn5bW9729Z2lDIzhfDqZ2YjTzvHRQHe0qp7Hh6uozRRegz0ZsUyo9gbimbnuceFKFHSoyiVykjR1CfEOdfHnPtZstcWwQDOjB1x+pgZfzi5NpsmPmkZdkuXPcAp7vro8573vKawW62hbCLKE6VCHchiAESWGVbnqRsjxIPUjJg21u/EI4qPc/0fxvL1sGOEui+EMQA8ZFFmYxla7isPcvEe8uj+979/azNpxVF6kxd+ikhcW1qCKX99n6Q0SU+BpWi97nWvaykoxOq/ZNnsnpnkjAsUQORe6RWe4Kstx+T+kwcDl8Li/jY+MLKQFRzxjD+8lDzX7gPkXtdn1Fk/UGeYoJSfwggPaRkU0scwbozL/vRrY5e+pz3xI0onfv1JXXOfmNlG/ThBUdp6660bP7zVJwqbsQW5p5WPfHWFpTIhBmGUauOqCYoo1RRKlD4gXnnS7zO2Uswp+IwocUj5jVnKA0P9AI9VKP1Xf6Z4mUUfUwzwzTffvLUFnIwFfOyRCQLyGWnqnPrG4IqBT4mVdwxX4xniMqpvab8YnC3izD9te/GLX7y1s3GUYqn89qoZt2BgTKX4w9R9Z8zTbvoDUj4KqtUJ96Cxj2GBcr+qBywQLKKYyl96bQs/44PrrCTA27Xnn/wYs66RfswE/AEAACAASURBVN8TRVscV1X3NpkMaXsWEAw9T+RtLOgJ7sYbfce4p+7qKi08lM0zSN2Sv0k751YXYaMPe8ZMMw61jecBFzJ9Tfk8Y6VXFm3jnEw4Oj/wwAMnRbT38YlPfGK7NpGlnGkf+/0o9MgzxRinr8NLucmaticQf28wwDpGszQMZf0B9trMM1BZjRmeMe57E2lFaxcC/7071q4yVWkWQCBKpFkZN1t8/SWjsLohMxvj3IBOSXWO4gtsxoQsy+OZjaAAGQgNBhQly8RmWqV1Qxvg3fwhD11x++67b4ImRzNEBkY8IYqcGbRpRHYMBkaQ2R5pDazyULYMIlkCNVhStimi08jAGYVYvMHPQIZsDFceD/9QZnAMbvLsFWLlTloPlF5BU0/1hacHm/JrA+kpHDCNIiMvDwdKbBSyzGqLI8PMnzZJWwsPGWizvA8P8pXV4Iuc95uALZObPWX4jB+EypE9DB4a0qLwuaZkIIq7MoXGZXv729/e0mc536xSZCsnfBDZlBCyPcyywsC4CzGmxJPlgdsbg+mPjsqAL5vlU24+/MJdM3gYc0hYZnX1bcqnlYlnPOMZwxvf+MbWZinDne9858afWWRlSV+mrGhf9wkyGw4b7ZL+1BtMjBZ590Rx1f/cZ/IXbyVQH/STn/qReY1rXGPqPdbLG59rNzKzaieeQkbRDclbX4eBvPQT9e6JjL5/Js6soJXDzEAKZ8DHaGRc5zyzkNrFrCQFilxuPNrXfaItKAsUUv3SpIHyhRhbxjvuDeO+p29R3slF2ox8bQzH9AvGkn4ZSjgFkBHPCEUJx89wjNLlHlMm/ZFceVDas+fJOBCKwZRr7pDq1ZMZ2Otc5zotSDupf0/Gtn72nmJldTeU8ZcRPSb9jxGT/iue0QN/JF+TAyh46geZUGEwwKQnCm6US+VS/1lkkkL/CGU23XXyc05GZtb1F2UM6fvqmPYwrkaBxeOeizHsGn6uGVDkaqekFQ8PBghiIMa4cM0VzT3d9znhiLEnr9z/wuSBP3UxodCv5OLpiWF00JnGJwOBYu7lDiFtmPGVUg5r9c/Y575V/jGlrozMPL8ykeeZ7acfec4jz1j9SP9FcLKqzsh1rq+TAwf3j7AlyyYYsrrWEp35pw9ljO/DnXtWMg6ReyhGijqYmCDTvYzynDUeqLfneij45rqOaw6B2Xf7mitT5bwcCBgIohBnAGD9e0BzDYhCHIMhN58Ht4cD8paZLMW6wQ0QBm6yPaDNnJjVMvCYncoDJ8XEz4d8GpnVM8ukHGR4gMRg6AdyaXuDwYD2lKc8pYmkgJv1ouzIS7kpJsjAIsysncE89cvAbraTYRAyqMcooVxYllZHMihlBjHkoSMs8oR5kJrJQcqe8jPczM4xpDxA1NMSsIFRm5gt527gIZFyWQqPIi6f/sFFvod9/zASFvJg41ZiYKUkyY8M4cg5ZRoZ+M1SmWU0o5c+0iKX/VFgMuAzPKXticKUVZUoYX18zoOFdjZTlwcNQ0EchYzCoA31By4V8rKSkZlW5U/5uE+Ihz9DR9mk9aPUivNwhqfz9L+0l9UI4R5E+rr+hGCmTn6UIeVlkJr583YkfaEns+1WGciS1oMVZUXKzCzKbK42YxySC3P3i4c+JcvMaXCShqJMbvoyIzF5ufeSFyzN7sE1CoH0CxEDlXyrCCHly9tK0hfdO/jkQ4mJwZCyitMfx+Teo+D0CpZ7Sh2QGV73gHtefWBiNcKqRwxGWInDJ95YZgyCVVybUg79l0IYw7MvjzD5xmCQVrmR9KmrWdjMsPfpo6jojyj96HGPe1wrU1Y8jIX6gZ8ym+2myMXtR9qUtzcY9GF9ThhKPzdpQ6ZrhkzGl8a07E99+/bTB4zXSBp5qWfktogz//R77d0TZTz1N5vcK6z4jAV5kxaDLc+IyFDnrIgwknK/pCzhc6SYyyNEaVTXUJRE5WdQI/HGthB3GeWFnXHDPdVPWElrtS8ELxMPUZgTnjbRt43ziAJvRSrknlYf92VPlFrjgA3j+kX6hj6F3woaglWM5/D0crZctpqYe8+kgr6f1Sd8jNX02bi2Ge+0ofvMuJexGn/6EENAuuwnkrcVF1hk9VP88cv2JCATFa6XLnueuw8ZTihGrzZwT8LcPamPG/sZgDEgcz95tmYSrQnp/oRbwUa9wWCSRRuSpRzcnLhLoVOWTW7CJav6LbD+1hoE5moHa02xqiCLRcBNSWnMrGafzuyRgcby4pIlS9rNmYEsbh0GbTetgRmZjTYwG3DMIHqAusH33nvv9nDyQM8DJXlJP22FgRIsjszMvBmsYzAkfY4MBgML4meeWeO8WYJi4sEYf38rJconj+xRyCAamXe/+90nD1hh8oeZAS97DChWlvjjQ4svCoLzkLJRdJEHULCkpCgD5cIgjLL8LR9uKmYFKWQpH4PBA8i1tBTknrjweFBkYO7jzM4Y5K2qeJgZZMnw8IkCEYPBNaWEIqhNlTkPTzIpZ1EgeoMhPPpPHuBxZevLMj73gICv2XoPG6SMHnRmo/JgoKApM+PWcr7zGDzSZIXHudl3igolwGwbAzKKFAVaWm4JPfXpucDAGuHNCoM+6d7Qp2wQjJsRPrPdwVD5GSfaV3ozcNrZuXsEZaMxo5AizUgwG81gRnFxaxdn/rmv4KvdrCwgeblXzaSSr73IhGmUqjOTL3igYJPRK5Ou9a2eKAqUemOBiYLxqzSlsYIyJvUc91FuDzEYGOZRON2n6uE+Peigg5rrGbkUA2MXWYxLxrXJDfdt/NJjJFEE9YPeYMg9SMljjERpMuaQz5jvyb0znvAQry0YAemfSeO+NeZl9tVRefUBZNbUChljE4bKkzL1+3DwUp7NHPekLaKwGVfH7prqazIiZEUiBkPC1JPLzJisrEWhTxyDIUonV6eHP/zhiWpHSlxWGODPXaUn5ckKVVy8Em/MyLghTPv3ZTVDPTZg8Cl/9shwu8kEReLkF0MOpiZ9QuTZuxYyLpjs4aJGrvsJpU0o3TEYGGd57uFhMJA3NhjEcbsxCYQiy2o+/rhDMWailDfG0Z9yZyXIhB55/cq4dg4+ng/GT+OQMcrRxArDtCdlyf5ExkHIfif11689H7RbypaxS193P5ioQOLlr28rn7HNPWm1173LoPUcQXkuaV/P7WmkP2fvWG8wxPXZfey5y7DU74wFyspYib7Q96dpeVTY2YtAGQxnL96rPLfc/GZJKSkhSrYBw88DbrzCgM/DkCISn1BhmfWMoiPMxuXwUC7H74WXR5aU8YcoHuJCBiDXZh5RBt7E9waD2fesMEgTf3+8UTC9yYGiIT6KggHGYJaBxgDtoZfZLHW29G8ANpOS2SFye4U5KwzCQ9LFv5v8/MwqKYPBGTEMLJsLQwZ5+VJ2U+feYLCp0cMh7RdfYbNLGZiboDP/yN1nn30mQVkVMtgi8ZRrpIwG5d5gaBFn/s0yGMLTGwzjFYYYP+F1VEf5+zEY5b90mXLtgZUlaXzxn4ZHDK7+4YmXDER5jkuR6xi7ZsYRPg8ZD3Dk4UbxZXQis/8xGKyoUCy1UUh6KwzpS5nd0s/NqoU8kPGqT/ynYzBkLw23rJA2Th34Hjvv9/rYt5B47h+uQ9lbAGPt6oEaxdHsuRlIBsF8JB35/SyqGVayooB5MOOBCxLXr8iZCBBPIR5TDIbcW+IpKplFzipR2km82cQYqO7LtIs4e0+CR/LtjUjKCQXYvatf9cSItNKWFQbKCAXO+Bbipkd+fPB7Ge5dyqRfKCsvUarNEGfswmPMcd/qL8ZIyqr+nHt8bGBToCjElDBEmTWLGxcbinxWdxrDsj/3X9pdWG8wpPzq1Ldx0maVMteOlHFjESLLfel+QfIhK/u4ltdg0FdTJvIYDFHOXVuNI783Prll6nNZqYNn7oMYaYzQEKOrn7AiLy+lwKMN8uzS/jGOxMWINLYjBkM//s9aYcCbtxFm8kpY76LjHjDGxu1H/JgYaHG7pJTrC+mveIO/87yQo687XCj4PcGbweKe6125sv/EGGGMct/EYJDes1X94dcb4K6j5ONjVBhbTexY9cuenTyXTALNMhjce5HVGwzy6I28rAYZv00kacMYDNOeMcpVtGYQ+J82t2byr1xXEgEDRnzA3Yh+ZgkczSw6GjSWjFYYZGvQEJ8NocI87LhCCPewcnQDG8CQh00Mhjwc8ExbYaAAKkvKY9CKK8o0BcQyZWa3zDBSuFBmsuRj8HLsfW9d+/Vv7smARpGQb95GQ2GJT7d6S+ehaXbReVwvzNiZAaK0x1gxc5olZXXPjyJpJlV6CgC8cs2VxIDowdkrqd76Y+begMhdx0Cc9GSYrZxlMORhgF/d8AdbeAnP6okyMhg8aDIThidEaYgC1xtMiYdN3HkYnmT7TWvvpKF04cnGTTPEecuRcGXVDupo+TmKwTSDQX88aNmMdPJVV1hlXwulS5z20zfSjpRRG2XNMJuZjxLCIKZ0JI0+HmNY+V3HPS8br4UpM/nBymqXc3FZFYsRpAzC5RGFwEwyI0b5Eyc+CosHqGtx+o9zM+HaLwZkNutaxRG/0FuT4pJEEUdkefDHhU3bksO3PsZqViUobtpHneE9bQ8DgwEuvcHAeFbP9HWvcpUHPj/n7knEyJKPsGCiD4Yo58IzfugzeHsFJ7yO8IK9mVBE2VLHHtNeqYpij5ei4p6lvCtn8swGbjwMhNQjdXEvIu4/8uknK7St8vZklllYfr3Ljv6UCYmkIbNfIWLYxcDQnoisnidptZl69KT+lLxQ7qP0BUp+VmAoxJlRDr+8YkBlFl8eVvRQyuScrJTVNbKSQIZ20s/1r37WnJIvPhuv1R9v2tHzR3wmTCjdrrMyoyxZrdX+0ovPL5MIykKBH68w4JvVv7iDKUffP3oXJGNsr5TLAwUTM+nkxyik5PcuSVkp+G+q/z6f4eOX8mdSKn03sq2Oul/V308bSmMMyMRBXzaGD354o8gzCScdGcnTyiry3HRvozxfte8sg8HzPC5JeDJh5F4hO/eQ80wOqk/y7Y2zlmn9rXEE5o5ma7w4VYCVQcAM8N7LXIe4g+ShTBkzGJhF6hUy+VCeMjM/zpei5SFEcc6mKzxmgvqlTzc4uZkRGMuRt8GMe0d8nbn7ZBa35zfDENlLl83iWooNmRE1e0uJMwAig5YfpdHMTmbKlEm+mZ2gENq0htSXgh5yzRgya0uZQnGBoCBT0sjvVxwykyafDJzOPXy4/2QG0Uy4WSvLux4MGZQdzfqon3QhDwzKsbYjg7KZNOHJ0SoLw84Ajzy4KGD4hZmFReRrP7KCR4s482/pMpxjTDEoMksfDODTz2RrB1hLN43kR4H0YBs/eM3YKnM2Z8vXzKi81Cd5kgt7fMFXv9OvsylVWfUrfYrBrG4w1beihJOjLPoFhZCs4K3Pmu2LEo4XMUQp0CHtoE3MSkf5T5s4wj2YSQMfRmW/kiA8exiUQZzZzrSReKSfwANGjJ2QelLs9AvlV3d1xr8QqWfGgp4XjmZm44KjLsGHss+A0ZeRsmQGuJfhPJgk3L1izDF+pD2txsAwypk2Sbs6CtcW0wxaK6PaNCsNyS/tKN/+3AZQfa8P0x6U0vFY1/NIQ1FRbn1Rno4h4Wl3/d9YlPtGHShmXCTxRa72STv2debepjzjDbLKkLEtMowbfTsbN+XT38t4YqClvI7Gl4ynCXcv5P5zNObpv3GJs4qSTcHKEt6k1w4MxZB662NZaUu4o/TiQsHP7Dp8jampW/oDXvekOqWO7gn9J/3DBEhfL304uEkXd7Hka58GIyJlyXMIjjnHa7xS3z4sMnKUr/uxX9FRdu2lb05Lm7YkQxnkoW76Ru4RcdrQvYMiR3t7NmUCqEWO/ozvZBmr9E39XJvqz8hz3uRNnktJjsc4G0r7uNYf5Kt9kTo4zz2UtiGjfz405jP/PGfTZnDrdQRpuEJ6RmZ8kocywMH45thj18uu8zWDQBkMawb3syXXfgBYFRn2N29u7lWdh3L2+cwqd/LNwNXzJb2HtHOGlJm8fsDq+cfnBvFersHbDEm/qpE8xmnnu16RNKnnfHJn8Qjv8xzz9XF9faflhXecfnw9LV3CeoVAWJ93eHKcLy48q/KY/FIfD9qxIZH8wpPrHCMj1zmm3vY49Js1E7+Yo5nvuDJEnnSz8pwmcz7exOkDOZ8mow+bxjfuQ3im8UXOLCxTjlnx0vdx0/IQPy5P8s2xT0dZNxs9VjbJ6fOaJrOPj/LYhyW/+Y49f1+upJFvnzeePg2+Pl1/HhnjI5cjM+ZLzzT+4xoSl52eX95RYoUvT/4LlaWvV5/nQul63mnnK5s+MqfVNXGO4tVhvvzmi+tl9eeLTcPwMWZlrxmjPasZvUHSy+7P9aPklWMfPz5X11ltNuYdX89KN+7LSbeY8oS3jqsfgTIYVj/GZ3sOufkozLNu0L5Qbkppwj++Sc2aRVHBg5KH8zwknY+JrPEvssa842v5opQvefblE9bLH8twrczcqPiI4g8mkRO5eFO28Ajj+mHmzSyacPx9GjyoT5P4Pqwvp3zCE3kpz3+lzVUAEtYf0xbCyMh1HhJ9fs4THhnJL+VIWcOXcHw5d8wvchwjKzKERcHALz5x/Tm+MYn3C0aOSdvzCsPXU8opLHKcp8xpX3HShz/XePmjx9Uk8cKT17gsCceDXCefrLL0BkPSkz2u21iWVaPeLSTxkfHfHOf/T3uGKzLkHzk56kOJx+86cUnfH9PGCUtaaXKeIx555uc697hzlD4sTTDszxP2X+7//fd1+V/of/OTxg8P6ssT3rh9ZZUx4eMjGUmf4xjfPk14HKVNWVw7V9+UK+l6TPGg4BKeHCM/1/0xceO2SHuameY2RNnkwueYb66QI+++LL284JD+3eebc2Xu0yc8+ec6WLhOfRM3xiZlSHzS9OHO5T0OS5pgOZad+FnHXt7ypO3Tka3+6hkMxc+SJy6/lLsvX/DlDWAvCBdPbo/cZ60S9HmQE+wjS/yYB5/yOaJx2VxHTuLG7daXUV5+kScu50nf84sT7uc8vD1Pna8ZBMpgWDO4V65nMwIrO/DUoHU2N9gazG5l+8q0oq+ozBVNN60MFTY/AtOUl/lTrJuxfZ9yTtljuEVBWzdrVaWGAMV8PuW9UCoEVgaBMhhWBr1KWwgUAoVAIVAIFAKFQCFQCKznCJTBsJ43cFWvECgECoFCoBAoBAqBQqAQWBkEymBYGfQqbSFQCBQChUAhUAgUAoVAIbCeI1AGw3rewFW9QqAQKAQKgUKgECgECoFCYGUQKINhZdCrtIVAIVAIFAKFQCFQCBQChcB6jkAZDOt5A1f1CoFCoBAoBAqBQqAQKAQKgZVBoAyGlUGv0hYChUAhUAgUAoVAIVAIFALrOQJlMKznDVzVKwQKgUKgECgECoFCoBAoBFYGgTIYVga9SlsIFAKFQCFQCBQChUAhUAis5wiUwbCeN3BVrxAoBAqBQqAQKAQKgUKgEFgZBMpgWBn0Km0hUAgUAoVAIVAIFAKFQCGwniNQBsN63sBVvUKgECgECoFCoBAoBAqBQmBlECiDYWXQq7SFQCFQCBQChUAhUAgUAoXAeo5AGQzreQNX9QqBQqAQKAQKgUKgECgECoGVQaAMhpVBr9IWAoVAIVAIFAKFQCFQCBQC6zkCZTCs5w1c1SsECoFCoBAoBAqBQqAQKARWBoEyGFYGvUpbCBQChUAhUAgUAoVAIVAIrOcIlMGwnjdwVW/VI/Cf//ynCc1x1ecwv0T55jc/Z8UWAoVAIVAIFAKFQCGw8giUwbDyGK4VEv7973+3clAknf/rX/9qx9Wl1I7lRoHtjysDTOpDxt///vdFi0q5+vSLTrxIxsju65p8FyniLGz/+Mc/ltsIkGew0d5+KdNZMliBgMha2bqtQNaVpBAoBAqBQqAQKATWIgTKYFiLGmNFikJJ/Oc//zkzaZRbDFEAZzIvZ4S8Q2T31wlfFcflUVj7+q6KvKfJCI7yyvnylLGXmXSLLTfDAs3Ke2XK05cl5Uk+fZnrvBAoBAqBQqAQKAQ2LATKYFjH2/uWt7zlcI5znOMsvy222GI48cQTm0L7iU98osUfccQR7XpWlWN4kHf44YfPYhve+973Dt/85jfnxEdRFTitPMKe8pSnDH/961/npJt18ZOf/GR417ve1cobJXkWr3Dlef/73z+Ed88992zlUKcowvOlX564853vfMMjH/nIliT1XtE8ttxyy+Hyl798kxUlfVZZPvKRj7Q6XehCFxoOOeSQdq6Nkfyj3KdMs+TMCk/7i3/wgx88XPGKV5zInJUm4Sta/6SvYyFQCBQChUAhUAisvQiUwbD2ts2iSnbf+953uNKVrjR88pOfbArze97znuHtb3/7cPWrX70plIT84he/GJ72tKcNP/jBD5oCuJBgyv2xxx47h40yGYVW/NOf/vQ58b2SKv7hD3/4cOSRRzbDgyK/9957t/I85znPaelmKZjJ453vfOek/BLM4k8hdt111zn8X/jCF1qdGRBkTlv9mBYWefMd3/jGNw7HHXdcY5mvXMFkPp6b3exmw01vetOJrDFvf32ta11ruMENbtDa8+c///nwyle+cvjlL385X1EnbRZc52XuIp/whCcMytbnn+jesEiY46w8yJgmp0+rLRbi6fnrvBAoBAqBQqAQKATOPgTKYDj7sF4tOd3//vcfbnSjG51Fttl5ijsl7Iwzzhje+ta3NkUzjF/60peGHXfccaAYone/+93Db37zm3YunZnrl7zkJQODhOIfetvb3tbk3vWudx0+9rGPJXjOUfqXvvSlc8JcbLPNNm3Wuo/Yb7/9hnvc4x7D/vvvPwmmBKsXOW95y1uGL3/5y5O417/+9cM973nP4VGPetTw29/+toWfdtppw53udKfG/+Y3v3n46le/2hRpde4V0U996lPDfe5zn7bS8ac//Wki89e//vWwZMmStvph5eChD33o8MMf/nASPz456qijhq997WuT4BNOOKGV6UEPelDDWkTyhT9FOisfv//974d73eteA15085vffLjxjW/czqMwM0jueMc7DoceemgL/+Mf/zh89rOfHbbaaqvhete73mDFiMwPf/jDrZ5kHnzwwY1X/XfYYYdBO4Uid+nSpW3l4JnPfGaiJse//e1vwxOf+MRhp512aoblPvvsM9zkJjeZxI9P/vznPzcc1eNlL3vZOHp40pOe1NpVXUIpR661gZWSo48+ugWN48NXx0KgECgECoFCoBBYswiUwbBm8V/p3Cn9lEjUz/C+/OUvnxgMn/vc59p5FE2GAGX8ghe84MC9xbnfZz7zmSYncVxvLnKRi7S4PfbYY6AkXuxiF2vX5z73uZuyO03Jk14eYzI7fpvb3KYFU9KvcY1rNFkXv/jF21E6SiQDxbmf/J/1rGe1NNyvNt544xa2ySabtHjGBaMj/Be+8IWHF7zgBcNBBx3UwpSPTIYAnktf+tLDec5znnbOxQeptzBY5If3fe97X4sf/13lKleZrLAwQM55znMO8oWXdIwcJO/8XB922GED3M573vMOF73oRVu6C1zgAnMUc3HqttlmmzVZt7/97Vv5r33ta7dreWy77bbNWCLj85///MAQwK9u0gpXDsZgVlGyAnOJS1xikm8MsU9/+tONX39IWulve9vbTp31p+CLx5+2Y8QxbOQnDh6Rpbxo3FcYeuc617mGW9/61i2+/gqBQqAQKAQKgUJg7USgDIa1s10WXSqz1RRFs9Gve93r2mwvRZEi9ohHPKLNbFMqKXFmwilpzl/xildM8rjLXe7SwhgWSLy0Ie5M173udZtCmPhpBkH4pbcyYXb51a9+dSuT2XHK7Le//e3GFgX+L3/5S7tWrs0333y41a1u1a6jlEZmjJxcO172spdteTiXl3xDBx54YLtmRH3wgx9s570BcLe73a2FMYK4F0n7jne8I8kHewvMnNtzMVZ0YfGMZzyj8UpHVuh2t7vd8MAHPrBd9sYCo4WybuUgZJ8IA+IWt7hFC2JMcSULWSkhP/tJrEbc7373a9FWjcjTtt/73veaEcAAC+kL0nqLUuqHN3TNa15z2G677dqGeUZgVjnEf/3rX29pxY/rLv7Od75zW0FwjvQreTECH/KQhwyXutSlJm9v+vGPf9z6DpmoX21hYOy7775zVkMaU/0VAoVAIVAIFAKFwFqFwP80rLWqWFWYxSJw73vfe9hoo42aSwzFn6uQTbQUOG5FZnxPOumkdn3yySc3QyGbbOVBIbRhGP8Xv/jFdu2ckh36wAc+0GaS7YVA4q04jCnKpXgK6fbbb9+USzPVwii8iNHAoOGDj5IuG5WFZQ+D8sdnntLNkKBkcnkhk4sS4kLjOkTZd022DbyUccZJZHFBEv+d73xn4Kpk5cK+APlJQzE3Kz+N1C17OOw/IIcB8eIXv3j4xje+MUlCTup2wAEHND5KMpIPYuwFFwYQFx+rQ1ZJ4lbGCEGU+hgnf/jDH9pqSAwGZehdxBhHwtTXvhErJ2QqI2OR25J45XB8wxve0PLI36Mf/ehJuRKWIxco7mvcoMi0CkIGw4WblHOrQc973vPaBnnp4MBYyKb3fjVMfPBwXlQIFAKFQCFQCBQCaxcC/9Ow1q5yVWkWicADHvCAthE27BQzbxiiIEchZAg4t2+B8ujtNyH8FGbxXFSiQPbKp9ULim022OKdZjBEpngz/IhiKI83velNLQ9K8Le+9a12/vGPfzxJ2jFKtQt5khNFUtm4/1ilMPtP6eX2EkV3bDBkhUHeDKm81SgZmvnm/sMdR/0vd7nLtT0eykvJplDvvvvuYZ9zvM51rtM2VAv83e9+1zaZX/KSl2zlNbtugzeStx9KeZwHE+cMDj/15OrExYfb0fnPf/5WPm1197vfHWvbqxKDgdKu/gyG73//+2fB06oE/NTF6eA9hwAAIABJREFUngXn3J/I3nTTTdsqgDB7FxytBKGUl0Fm0/M0Ysypp3TKxnhynlUEfUe/FOZntelHP/pRExVMph2n5VVhhUAhUAgUAoVAIbDmESiDYc23wUqVwEz4DW94w7PIiIJKYcweBisNFElKKaMCUdziUhKXFUqemeIQ5Z1C/LOf/awFiZ9lMJAnPqsHUfgl5Idvtt8sMwX9qU99arJoR25Q0iLuQc6TnhLuOi5MeCjYswyGfg/Hbrvt1mbLTz/99IlCfNCZexyWLvP/ZzSYgYfJYgwGrj9xSbIPgtId4ssPq+9+97stCB4o9aHco4TLN25YMIlblHIg7RBXMZvb5zMYKOraG2V1wmZrG9Cvf/3rN5ehxCtfXJ3gatUmZCWHIcBVKuVMnCN+7RHyhi5hp5xyyvDRj360GTGJs5okLm/HEh6DKbIdc550dSwECoFCoBAoBAqBtQeBMhjWnrZYoZLY9EwZHFPeZkQ580YfSht3HoqZcysQZu3zjQZhZtqRc99sQPht4qUEx8gQ7y1GXFBCvcInvt8jER5vSfI2IxQfe+5OX/nKV9osvXRmthF3F9fKZ2XDNxxc26CMf+edd27X4c/GZ3Uw+85gwa/+XLGc24vhdauUWsbGVa961VY/BoMVFD74+CnZcMXf16sVbNkfgyEbscm1GuGtSpTjuP9YeUB9+rzJKbzZx8F9B0lLnr0L2iabkb35CHlrUQwGrk02hHt7knaQjsGg/Mi3MoS5psg7V2arTAxHG+UZcAwIb6mycsPIEJeVnuxx6OtANlnepsSdK29vEqZtrAI5Z4QydMS7nrbnhWFivwe3pqJCoBAoBAqBQqAQWHsRKINh7W2bRZXMngWK35jiS859hIJNaVuyzG8fURrNZgvzi/JNmUbC+hUGr1zl/sKNB3mlKR4rFb0ymXNxlM5Qwr0tx14BZJWBPz3e/OJ6I54LC99+cVYIGA02+YZXvRlKrinPp5566uStS1xw4tKUvD70oQ9N0kpjtp5MZWOUZIUBvxUDZckqgrCett5662GXXXZpQVYE8jYgcrn9+O4Eoqyn7q61g/0IqYMZfBj2rj977bXXJB5fPzPvLVPZNG3Tszc7aTOrBXgZQskvKwwpx/HHHz954xVeblX2QSCKu/0RKZeP/skr34fIKk9jXvbHkAqvN0Q99rGPbdf2dqDsWQmPlSTlDcWogT+efqN3eOpYCBQChUAhUAgUAmsPAmUwrD1tsUIl8TE2M9Jj4rpDmeRX7k053EYo1pREb82xwdcMsLTxgTerjSjQUSZdMxS4K0UZJZs8hkdP4imX5GeDdB+fGenIEUeumXT7LMZEoTTjbYYcMSKOOeaYNnttZly8mey4BOEjS93EKQflNAqqvRPKLU1WAJTXBl5YWFlIHeBmRUV80qd8VizytidhFHYyzab34dKR5xcZFGerIHjla5O0cvVkpt7+jriIBS8rRXFpIs+mdjJgod6+S5E8f/WrXw1LlhmIyZd8b6LCR37qn/JZlRGuHvCz2qJvIbj0pD9pF/XIvgX9KOf6mXySV29wKGvKRI48+43ifT51XggUAoVAIVAIFAJrBwJlMKwd7XC2lsKsLpcirxRlVLj2ZebVSVF6k8f4OuGr4xileCHZi+VbSE4fH5kre+xlzjof5zGLTzjeNUVrMu81VefKtxAoBAqBQqAQWJcRKINhXW69FSy72Xxv3/Hdgytf+cptI3I/C7yCYudNNlYSx9fzJl4FkYvJD89i+JanOJG5ssfF5DnOY740q7qe8+U1jks5x+F1XQgUAoVAIVAIFAJrJwJlMKyd7XK2lyoKZI6rugBjuePrVZ3fWF7yy3Ec71rcfPHT0swKi6xVdZyVTx8+zquPG5+vqnqO5S72OmVdLH/xFQKFQCFQCBQChcCaQ6AMhjWH/RrNOQpjjmu0MOth5lGIV9VxPYSoqlQIFAKFQCFQCBQC6wgCZTCsIw21uoq5thoMa2u5FtsOq8pQiJzF5lt8hUAhUAgUAoVAIVAIrGoEymBY1YiuY/KimOftOospft5ysxje5eFJWRaTZm1XpFO+VXVcDCbFUwgUAoVAIVAIFAKFwOpAoAyG1YHq2SxzmqLdh3mV5SwKXwyGbH5OeNIJT1iOy2M4SJM8ItNReOTl2MfPOp8v78hJXWbJWNHw4JnjNDmp16o6ymO+Ok8rw5oI86rUntR/Wrv3PGvTeTDOsS9b+lPitH/fvj2v8/n6R3iDjWPkk7kYCp90KdOsdJE9K154yjuWJW3yyhH/YmTiKyoECoFCoBBY9xEog2EdbsP+4T1fNRbzYMfT843fvd/LHysUfdys8/nK2uc7K/04XBoy55M7X9xY3vJcJ+8+zTivlG0xx8iZjxdPj3uUu6Q9O47jOo7z7OP78zHf8l6vSlnz5T02dsa843IsZDCsSL9OnuO8Ej7tKJ+UZVq8sMX22T59+tu0sUBc4vs0dV4IFAKFQCGwfiJQBsM63q4+LuaDaD6ylQ+YqVIe5vMplr1SQlny4S/kPOlbwJl/vZLgGw59fj3ftHN5zadAReFJHpSU008/fZqoSZgykOsjbSFlh4cPqPma9OoiH6/rP9ImHx9DE46Ua7E/H02D5Xz8ZMJvIdyDH/5VRf1H/BaSKX/1QOkf2iFKZ44LyRnHw9YH5VY0/VjetOuUW5wP3/lI3ve+9705rH0fTl3TbnMYz7wIBtPihPVpe16y5yPplGUhvuSBV5qe33VP4/ikdTQ2uK9gsjrvq748dV4IFAKFQCGw9iBQBsPa0xYrVJJrXeta7cNrN7zhDed8MfiVr3xlC58lNIrDS17yksbn420bbbTRcMghh7QkvWIUGT/84Q+H61//+hP+u971rjOV+igjjpToa17zmsONbnSjiJocw+dryVe72tWGi1/84sMlLnGJ4ZKXvGTLZ1o5JKbEPvCBD5yU5brXve6wdOnS9tXlTTfdtIW/+93vnuSzKk6UNeV9xjOeMVzsYhebXJPvK9JwDIV/1jFtIM0ee+zRko15IytHvHvuuWe7TPrEOb7lLW8ZPvShD7WglLWP78+npe/jncN/v/32m3xhehw/zoPMl73sZe0L1Hh9JVyZTznza93CUkfnoYT1ZerPDz300CaHwYTG+UbOqjgyTm5xi1sM5z3veVu/JfOnP/3pcO9737uVQX1ud7vbDT/72c8mdZlVHrwLfRTRF71vc5vbTGTf4x73aMaRfKfJfcELXjDhVcb3vve9WBckX+ZWHl9Mn0V3uMMdBveP+3CzzTYbtthii2Hvvfce3vWud7XvtkhPTlEhUAgUAoXAhoXA/7SbDave601tb3WrWw3bbLPNpD6vec1rhr322mvYcsstm3JA6eoVrwnjspP999+/8bz61a8ePvOZzwwPetCD2vVXv/rVnm1yTpG/wQ1uMBx77LEDZZzyQIlCUfgmzGee/PGPfxz22WefxksRGq94RCFSBvKU/41vfOPw5je/eXjta187VWGyikDWBS5wgaYsHXHEEcMFL3jBVrbkz7Ch5KDkkbiFjgvxM0w23njj4ZhjjmkKtbJTqilX6hAKJjnOMn6e+9znDp/73OeSbN7jJptsMjzvec+bw9O3r3h9IjQrz8TPOvbtpE5HHXXULNYW3ueD/ytf+UoL1/6M14VWKRbCnLCrXOUqw+Me97gmt69zC1iFf1Z89J+PfvSjTaqVLtc+dqivvec97xnOc57zDJRr5Uj7pggU8he/+MXtfjrnOc85PPWpT03UnGPqjOfyl798y4/Bxwi4173u1VZoelwlPvroo1sfY5QxNB772Me265NOOmmO7PGF1Rnt4pdVk+Tf87qPbnKTm7T76nWve93wtre9bfjSl740YTnXuc41nHDCCZPrOikECoFCoBDYMBD4n3azYdR3vasl5fDGN77xpF4e6FEMHCk0s5QrCphVgp7Ofe5zD/e5z336oHZOeSePq0bowQ9+cAtzPVaaonBSGM1UUvApWNN4hT35yU8ett122xa/0B8FRlkOP/zwCevXvva1Ydddd23XyugL1qt6hSGZURjPd77zNVco2PZ4O0fBwxFPFL8PfOADzZDh1nHb2952sGpzwAEHNOUv8rmXmXFm9HEBsWKwZMmSFm32l3FCgb/5zW8+7Lzzzkk2HHbYYcOFL3zhptgyuH79619P4tIH5GXW/8QTT2yz6GFgPN70pjdt7ZQwfIwZddJ+ZrLjEvSmN72p5a8OUVatsGT2+773ve/wjW98oxkKr3/965u7VuR++MMfHqyIWRWKYQEfijbjEjEMKOnShj7ykY80ZTrXiz1a4WJkomlK8lgOgwEWlGX06U9/umFw3HHHTVgZ2Aw3uKatE8nQSJ9wP80yGPBza8PL+AxpO0aDuPSdlPtKV7pS6xfhdZR+33337YPaedKo+61vfeu2UoBXn5pF4k0IzCLjCzyKCoFCoBAoBDYsBMpgWMfbe2wwpDpmBz385/M3ftKTnjR8/OMfT5J2lGannXaaE+aCEmVmPYqX43Wuc53hGte4xll4BURZMXtK6aMIUi7/9Kc/Nf7E5/iYxzxmeOQjHzn83//9X5sh5xrF2JhGZnnJNcNq9tpsLv/qKLOnnXZaKxc3ltVB6vGUpzxlIjrG0UEHHdQwT4S6pX4JsyJD6WIMwDoK4wtf+MLGoj2EW62Ar3O/Zz/72S3ezDYD7CIXuUhzi7HScctb3rLF3fnOd26GjFUGK0EwQcHFOYPjAQ94wESuMMaPPCjxzsk3i8z1ZPPNN29x3NUe8YhHNMPnZje7WVNo9b2rX/3qLZ6Sqy2ucIUrtGvto50YLec///knLkpkyEv5tt5663a+yy67KMbwiU98opWPIUExjrtd4vGQG0NwjK34acQ4kqd+Pd/9kLT6uvLF1cdsPuMMngceeODw0pe+dDj11FPnGAvjsgRz+T7taU+L6LMclQ0mWYFhOL3zne9shh+XpzG5BxlyIRjL4+1vf3uCznI88sgjh6te9aotD7zc/6YRtyvxDCMuV1YcGbQ9wb8Mhh6ROi8ECoFCYMNAoAyGdbydzcpnbwClJTPJb3jDG9rDP8rsuJpjBUe8WW0uCZkNH6fJ9bWvfe0mm3LB1WFMka1scY+hNN3+9refsEahEmBFYLvttmvKINlWIsi+3vWuN+HvT6x2UGopt1ZJttpqq8a/++67NwWdUkhBshKwOkjZnvWsZ51FNEVPHOpnnuERTO5yl7s0nuxDwCtNDAbnvcFmZUEYP3JEYUt7uz5l2d4A8dl7cpnLXGbOKgEelPzNeJu9zoz2Qx/60KbQ94qhNqCsR7kmP37r3HMuetGLDl//+tf/K3jZv/geD9dRam1Il6fjF7/4xcYLp5B64ecGx0hh0DAaQ1Y27G0JMVziBpewxRwZn2QxtLbffvvmAhbjVXr9MRgxGPS9uLQpo3Rc4OByuctdrpX5Va96VWvntPW0cqhbb/D0PMmvD/vCF77QZGdPi7ieL/c3Nzi4kr/bbrv1IuacMzDwRMl33rddzxwXRXi7B+07wt+v5PWy+rR1XggUAoVAIbB+I1AGwzrevmODIcrFQgaDascw4M4T//soSfMZGi960YsGP5t+zYL3FIXGbPtlL3vZSdTzn//8ifuTMvrJg6JmdpV7R+8rbXaXcnLGGWdMZOSEci0uSrZwbh/C5E/hs/LBRacneYq3CZUB4xdl7oMf/OBgxcVmZkd7CsxkixdGibW/AsmnV+iSR28wpI45hocLGGMmJJ48s9hckZx/+ctfTnQ7CmMMIQZDFOq0n3gz34jBcMc73rGdT/uzQrHjjjtOohheDMWeuNuQ+dnPfra1k/MYJHkL1Mc+9rGG3+Mf//jGG3cwcpLWuRUGeSIGoxWRkLoj/Nys5Kt+PVkl4t8f0k+tcHijEHcp7fPEJz6x4cPA4RJl9eeZz3zm8IQnPGFOnyKDwWNG36ZehkNwi3zHGAz6jzJqf2V8xSteMWHLBmh9WJ9KXSYMZ56oT/rYOG58/da3vrXlY6XNxusx5d4SbiVKuRgzyhb3qXEa+xFgErK6ZQVuGmnTnhcP45FBHpKXVZGiQqAQKAQKgQ0LgTIY1vH2nmUwcAPycO9n8vuqRtmk+OPj49xvdh4rQGaIzVL2SosZYWnj+hL5FC4rC1Yrdthhh6aY2VNgZnq8ZyJpcsysNiPCTO40hc7GUPnG/13azF7/4he/aAofV5lpBgM8zJ56w5Lf/e9//5Y1hdjeDdf8782oU8Kc46Nkxy1I3stjMKRujlYYuP6E4Ewedx55UjDTZty+xFPyMoMvvl+dIEd6s93o0pe+9LwGg1lpinZIWi5WSL5+ceHhIuQaT9xz9BurOmb6bba3wZ4LUe92g5+xgRgMeKWj6OsTqO9H+L2ti5HmHKX/HXzwwXMUVnnbs8NwYShoL+3GCPAGJQYMlysK/d3udrfm5tQELvvr82QYyyv5hcdR/+WSFJc2M/hWPpYum60PMYilXRmDIXX0ylIYkmd/R/8mKLgxjmLA6+djYwIeVuiSLmXMviNjhNWVu9/97i0P7lWpW3jT53IdrOyfMTGQ1Rj9J6sV4a1jIVAIFAKFwPqPQBkM63gbU/TjokIBiRJiU+pYGYoSkCPFmwIQZRAUveIQPuEvf/nL5yhIwhgKFFjfguiJ+wellpLibS+UOgYDxeN+97tfKyPZKS8FRFn7NwUxBiiaS87c7Es+5Um6bHru39bCOCCDsmdVgsFwdrskRYlU1r5+yh2Fz+y/Wd8QDJSbYYSHYhrDBA9FTTzFHMH7Oc95TjvPfhLxDA5kzwH/c5Q828WZf9LzwQ/ZWEw5Dil33oBlfwXFnPwYX1ZZvPI2PvfSma0frzCkLfN2Hv3KPhWy0kelNdstzIpYDBXhIZj2Kwzc0PR5RI7yLg8df/zxk9U0Ljj6C0p7OVc3uGS1LW8moqyHtEfqkn7c3zvhg3dvTAkfl1ub22TN2NVmytKXR5rUk8FlBawnBjBDNN9xCL7GgHve857NgGJUcXVTZgZGXr1LTvqRFSB7UHrSZlYYkr/0tcLQI1TnhUAhUAhsGAiUwbCOt7OZxWkGQ2YXowyoprejmMnMm2dsOjXj7zWLXBwo7maVM3PPlSLuM96cQlmgQJgJ5zZjBSAKhhUIri2z/MvNkPd7GGzK5p7yzW9+s+1hIIfStGSZgcAQiK+/cnMjMdPPCKC4eJuOtwHZ7Ku8yiYt9wnKuVltftiry2CgYE97802MFmWOwhflTRhiMGiDkHi4ZtYfRpRCbwQ65cz9CZTOGAx4p60wZCXGZmF194aibBqnhMZ4kJ7/eyjt6q1ElHx7G/A8/elPbyzSuab0UmgZG7DHx4Uohql2N/Ot3viV5ze/+U3b48IoXXrm7Ly0Vgm4wX3rW99qRmRWXLS9tD3ZTN27tkU2nmkKep/WOXzh4FW9F7rQhZry2xtMY37XMRgyC6+cXLco3N4EZRXAK1ZjmGXfgb44JuW1EtIT5d1qi03N73//+1udrRBZlSHDD7aIwWgTO4MdMcLtQWHE4E96xj/iigXPWUq98mjHkD0ZXKBQXpTwvve9r/UF9zn+3hjUF2uFIejVsRAoBAqBDQeBuU/nDafe601N+xWGKKkq9453vKM97Hulio+8bylQAChSFHyzw5QCP77mlBPKOXr0ox/dwqN4Ui7zdh/8jJXsO2AwMFzEh/ry8FG3uhCiIJERxchstpnPlIVSbnMmGRRRM6XiGARIXWxMDb9Ze2+uQTZRr84VBsoZ44RC3BNFi0sQgm9+PQ+lM4ZT4r1FqFdiH/awh03qRdk0w04RRIw0r0btSZvlLTkUbG1MZtqmbwduYTEYY0xyr7KpN1h6xW02LcuHgiuOWxYll4tLeLmeKZtrRg4DQ1u4tlIBI4Zp3viDp3/7kz4U96WTTz65rV70daMQx8DickNu/2rfnnfaOYwpuMoQo2rMh6cnBkPvkqTPMXDyBihl0IYMWaT8wrhPjWXZU2L/Tk/eZsVYds/4jgLjw71HBvczR/lT7N2/rrNvRVtasRPmxxjT5iFtxzDKRmX8PemfSzvXKv3JfRfKa3EjP3tnEl8GQ5CoYyFQCBQCGxYCZTCs4+1N6R+7uKgSv+go3H0VfcE2CoY341AMKRBms/2cm6FHlA2KQ09cTKwKmMEeu0DwI4+CQcmiPEWB4iYUpTFKP6U2LiHywEO2Gd0+XByF2ipCT/jVsZ9Nl59ZWW94scKQ/Pt0K3ueGeV+zweZFM28sjJ1zzF5ct+Cc0g8YymY28jtPf6U0ewN0QbZcA2bsaEirPdr164MKu2T/B2RvKLoJk64MllZgmdWI4QjcqTLG7HUU93xclnST7jrMCy1raN21IaurWw5pt2Vn3FglUo/Rcpi/0rq3AKX/ZGlLshmdQZuaKwMJ3x8VMbevz/lCF+wybVyM0Z9MwMFDwq+OsM7e23Ew4cRRUkfy1KfcXstWbaS4p6Fo/6gz1jlg5O6+glnLMibQceIDMkDvoyY9LfE4WcwxFhMXVMusvtJBKslXAV7Umbyg3sfx7DpXQH7uDovBAqBQqAQWH8RmKsNrr/1XG9rxmAwe8pVgtJIMZj2AwBFMu5LmV2eDxguP94etBiiTJJNOQv15UhYjlxcGBi98pK48ZEyTTZFK4rPmCfXFCauFVxIzPivLlJ+M72zytPXfTHnUX7NSFOKKdNmmJ1z4aHEJi+8kTmtfomb77iYdD3PfLJWd5xyUMovdalLNcPFdfByvrwU/Galg7W+b7beCscsUm/Enc9KHyNiFha9DO52eeNS+Pv4/lxZ9eWs8vVx0865yvUreSnjNF5hVjpiTKUs4yM+BqXvOTDyuSoVFQKFQCFQCGxYCJTBsI63N3cQLgXefGJGcPywz3VfTbOOwmcpXcL7uJxLM6axnMhOvtPS9DIyA9qHrcy52V+uI/z4fditnwleGbnjtJR5xtqs+vX1X8w5jCMrrl1bLnPv4ief1YPeGBuXx3XST4tb18O4UXn7EUp/XF11okDbM2KVgWvQfNRjPl87T5ORevQyer7+3ohsaYSPf8IZyyGGeNIkbHwMf5/PmCfXNqVzDfNGLasPRYVAIVAIFAIbFgJlMKzD7T3tQR8lYdpRVaMk9NUOr7CcjxWThI+P+PxCffw4LNc54lWHpO/Tjs+TJry57o/SjGla2Jhnea/HMsfX5Alb3t+0tknZ0ta9zOQTnmnlSNy6fJyvzVdlvVYUv3G6vo3GcX15w9eH9ed9WhiEP8cxb49T0ubY8/bn4vt0fdxC5ylHn0d/vlD6ii8ECoFCoBBYdxAog2HdaasFS9o/wMfnEgubpniMecfXK5JmLMP1NJrGt6rDpuW7qsJS1rG8hK/okbwVTbtQunFZ14VrddrQadyuYzx6jPrzMV9/HZl92PKerwoZy5tn8RcChUAhUAicvQiUwXD24r1ac8uDe9pRxtPC13QYY2RVGSTT6rI6AB/nMy2PMc/adD2tvGt7GPw2ZEr/gUF/3mPSY9Sf9zzj81myxnwLXS82v4XkVHwhUAgUAoXA2olAGQxrZ7usUKny8J/28E5Yz7M2navwypYnhkd/jNwVAnRGor6cM1hWui59Hv156taHLe/5rDKvzeHqOI1S92lxG1pYj1F/Ph8Oi+WbT8a0uNUld1peFVYIFAKFQCGw+hEog2H1Y3y25eAh3f+ScR+2Pp+nvvz91XN1EdkUd7/QOL/F4ix90s6XJvmEfz7eheJ6Wav7PAZOj9WqzLNvh4XqvTriV2Vd1lVZcB23s7CiQqAQKAQKgfUHgTIY1uG2nPZQjlIURSrHhK/Px2wMXhNNOm6LxeLcl3W+ND1fzlembSPDcVz2Pq4/n8U3K7xPW+frDwJ9P51Wq8RPi6uwQqAQKAQKgXUTgTIY1s12m5T6qKOOGt761rcO73znO9sHufKwjjJJic6Me+L640TQmSd93LTz5eWPjKTL9bRjePrjNL6E9XzOhfsY1hvf+MbBl6TzoTFYrA7yJWN5TqOUcaGjtD/60Y9auZ1P4+/Lr04+TJd807ZJm+NYjvBQL09YZCV+1nEWn3Ay+/gYb76fcNppp82JmyW/Dycrv7Hsno98Hy/LF8P7uNV1rt3dc/O1/+rKe22Qmz6Xdl+6dOngtavuOW/60l7jPrY2lLvKUAgUAoVAIbDiCJTBsOLYrRUpvSvel4B9wbn/Su5+++3Xwr2PvX/ARwnzYBf+pCc9qfGR4UfZDoXXEVEMfEU2vJtvvvlEKe95x+e+dHvZy162fXwtyl/PQ7ZvJlzkIhcZznve87aPQznKJ4rHmN+3CW51q1tNynLBC16wffnWx+kucIELtPB8uC0y5LMqSFme8IQntK9JO/dF6ZRXmX3Ei5KMUt+cu+7DhEvjexrhaSfL/sgeh+F9ylOeEpY5+Aj04a4Xv/jFLT6YhTlKfK5zDD7JD1949ZP73Oc+Z/lysPikS53II+NBD3rQcOqppzbxvu6tzIyiaeQDgsk38bmOXHkJS3j4Eq7vnPvc525fYA7fYo4pf+Q5zkrX8/gy8rnOda72vQ8yHvjAB7Y6+gryJpts0n4vetGL+iSTc/J9tRsm5zznOdtx1113ncTnBF9P+++/f+Ptw5yHL+Umi+z88oG4cTrXvi7tnguvjwb6jsksymt/fdjuile84nDta1+7sfq43fnOd74mJ18sn4btLLkVXggUAoVAIbD2I1AGw9rfRvOWkNLsq7Sh3XffvRkBvhBMEaBUedBHoYiCgf8Zz3hG43nLW97SZml9vViaL33pS01c0rgg56IXvehwhzvcYfjKV74yHHPMMe0rsT4sFgp/fxT39Kc/vcm9973vfZaypDwUGwqXWVuKvt873vGOiJ5TfjPsDCR1PPbYY1t5LnzhCw8UntD1r3/94b3vfW8uV+nxlGVfvYWTL976mJrzm93sZsM3vvGNZnBRJnfaaaeWZ5RkA8dlAAAgAElEQVRe9YThNHrJS14yfOELX5gWdZYwivFzn/vcs4RHQaO49W3SM4ZnoTDxfVnV76Mf/WhLNk2GiP7L4fi//e1vN35tRUHOl4pnpZ8VTog4v75MTXj3t8MOOwz6/nxyOvZJf0pY+mGu5zte/vKXHxjkSDr1ZTR8+MMfnvTd1H8sx0fP8Cvr0mUG+Etf+tJ27evk02jPPfdsBuKlL33pxjeNJ2WPsWC1kTGQ++6zn/3stGTDJS95yWZ0u99PPPHEdi1sGskj+TzxiU9sZbnrXe86YTUxoe+dccYZLSy8E4Y6KQQKgUKgEFinESiDYZ1uvmHYbrvthpve9KaTWvjCsS8dU54pJlGyKFL9Q18Cs/7bb7/9JK0Ts553u9vdWljP//KXv7zJM7sYysxqrqcdKS6XutSlhvvf//7Dne50p8YyrSxPfvKTh9vf/vZnEUER6fmViYKjbkccccSEnxKfWd3TTz99uNa1rrVaDAZlOfjgg5vx9Nvf/nb42Mc+1spiJj3EPQO2P/nJTyYKbBQoytyb3/zmtgLB0DPz/qxnPWv4+Mc/nuTDCSec0JT+q171qsORRx45HHLIIcMHPvCBFq/ez3nOcwYGltWlhz3sYZMvQb/yla9sqyuXu9zlhuc973mDr1GP6dnPfnZT5g899NCJocmgtGICM22UlSqzzdpFnr4k3q8+kc9IuslNbjJ86EMfatl88IMfHCiTDCZyvva1rw2+mvz85z+/uculLMrJoPOF8t6o04aZbWcAXP3qVx/23nvvlgzu6LDDDmtfHFb3Aw44oIX5e+1rX9vyTX+fRCxwcvLJJw99n16AvUUzGLQZ4hIFH4bumNLmfbjVp8zMJ5zRYJVkGpnJl18mAMYye0NNu+ceiywG5uMe97hcTo4MBOW2IhdiiAqbj/QNK3gPfehD21ef0y7CN9poo0k7j8s5n8yKKwQKgUKgEFj7EZj/6bD2l3+DL+FtbnOb5uoDCA/pPMAprR7+vQIlvn+QUxq//OUvz8HQLP8jH/nIFtbz/vWvfx3ibiDSXoGtt966zVC6Tr7Oe6I8UgopmGa+8aUcvfxHP/rRw73uda9h2223Ha5ylasMu+22W/PVj0LUp2MonP/852+KtVULs/nHH398m+2XN3ega17zmnOUUeHJrz+m3I4xTvAifHHDyFEY5ZnrD2K8ZCUkKznqShnOrDq+5Hn3u9+9tUtcQRhU2umFL3whtqb4uqYQU5qd++2xxx4tnlJGYdtyyy2bcg4HijvSbmZ5xd/lLndps8ypX2NY9qc9GISRq4yMRK40j3jEIwYrNWRwM6HEqgdebjhxhbrEJS7RXLAoohRg8WbI3/a2t7W+6Fr9tMmvfvWr5i4Ul6TIUwarRHgpn4jRxLXLLDdjSv2V61GPelSLf/CDH9zK6qivSHvPe96zxcFRPX7605+267RXu5jyp62RepIDr6Sdwj4naIsttmiz9wKtoEj/mMc8phkCDPhPfvKTc/j7C2XkXsRwpNxb5VsMMbLkM27PPi1D1CpXTwyGGF19uHNtEnnGiRvd6EbtvhLHEJpG+p92svLBWAx9//vfbwYD90OU/p74OhYChUAhUAis2wiUwbBut98wNhjyoF6MwdBXneJzwxvesO1RSHhk5TpH+wUoLxtvvPHEV32agsagoIghymZvMAiLfAo+xdP+CAplFFpKcfjw5vf617++KYeUZUrOda5znVaenXfeufEwbK5xjWucxWAgqzegmvBF/EWpwqoM6s6lpKfU5ROf+ESL54bTU+JTt94Fhbx99tmnsTuPwSZg6TK3FWFWFRCDrndBo/CLtwqB7Cu5xz3u0c6n/TEYNt100+GrX/1qi6Zwa8/suRDIze1KV7rSZOad/KOPPrrxy88qVgwAgeJjTOSaAoko4fqJ1ZglS5Y03n415dWvfnUL41pm4zKFdJdddmlp/VlBsWKGtHOMI9eU7hvc4AZOG2211VbDgQcemMuzHKf1UUzCH/7whzdsGWqUbntkUNqtXZz51xsMjG7119/ue9/7tpUT12n/seLNYLBa4Od+s4Ig7JRlqyvzkQ3F5PZ9secf56NO2kk+43r3dRJHbn7z7WHQDlYKEXcnY0+oDIYgUcdCoBAoBNZPBMpgWMfbdUUNhl5x9qYlioWZaYobokhEscgxUNnzQCGi0POt7gmvHzcLCkuIwhuf57HSQznD3/t9U1ApMZn1jVxHPv/i+g2d3F6EWQmhnHJn6d1dUg7uJ4wYqxL5iXvXu97VNutasbBpl9/329/+9sFs9kMe8pAWtvcy9xhll48Z1p74blt1EJdNx4lP2V0zGMYuKdLAM/7tZst7Em/FBTEYuP2gKIJ9ntxS7nznO0/i5d0Tg+EBD3jAJIixwFhD6oZf3cmkwOsnzuMS1RiX/cGLu5JVCfFxJRLv+nOf+1xj5R5GIdYuVo8YD4jczPLjt8ISN5nGcOYfhZxLDsosOxc8eXOBQlmForRrP8bv/e53v6bcqquN/bB6wQte0FYztKmVHu44PT7aUBtzzbJXhzGT+6TnUx4KM2IEMc57Uj6rJ9NcneBP8YZHSP3TpvLp8wrPLIOhv5eSTlsxvq0EBaPEkdefu2a8vulNb5qsDgkbE5fE/n52v93xjndsbOSVwTBGrK4LgUKgEFi/ECiDYR1vz4UMhl6hSFWFRdnku05hoUT1s5wUpShL0lEeKQ29skEppMBmthqfeAYA5ZABwn3HjLiZ780222zO7Dj+WUTZsg+jV75TF7PpymzzdUj5hHGJkHbWHgablG3u5q/tl5UCm3qd77XXXk1ppDR/5CMfaa5AXIz4/lOqYCKfpJO/NwIJU0cK5JhgEtwYDGbKQ5FHGY6iPlY0KdxRyOFNWUPBQ96Z0Tb7TdlNfN+GwsjqMTWjr416Oumkk1p9KPD6Cfn2DiAuRoxLyqi+Q1mGdVy01BP/F7/4xcZvtYdbEaXeyoVVoTHhtwch9e/jvb40K03C7TlgfKqndFaYQte97nUnLkowSlvqtxR0hq42l96vN0Z7nPLmMC43uU+Sh2NvMCRc/cJ7+OGHt76fVZa0E15ltvenJ32CEauM4U1/CV+MpYTnmPgYTY997GNbHozhvKkqPP2RuxkjpCdtq3z77rvvJFg+XuXLGHM/u5e5Xdmjwyhxjowd+lK5JE2gq5NCoBAoBNYrBMpgWMebc5bBYIOqh38UkFSTUhNlg+KIx+bUUOKSLtcve9nLGi++zAwzFKT/5S9/meQtjvJi9p8SyUfbBlHuFxTqvD5UArL9+HyTQ2FMft4aJIzyipQnSl0U2k9/+tMtzp/VAPwMAkqL2dC8VnXCtOyEfLKSzzhOHvkFgyiCSSOfzDALcx0/e/JSzuQlLLIohxTbEF7ps4HXjL9Z+5AZevFZ0WAwMGB6Em82HFnx6d+SlDKHH6+2DNnroW16oqQzLGxkzaZe7j+I8t0r8LAxax6DBo888qYtSrlrfYKfv/N+dl3fEUaZn2Yw8MuPS5J9LjaEh7S/FQsrM+jKV77yxHVLucbtiEc5+vbv8aEo279hDwXDL0q4dD0xGFLfbbbZZrKPBw95Nt9bRdJ2Y2Lo9EaOeIp3VhjST8bp3E9wQrn/HPvyW0GBR7Afy3AdfgbTuC2ssAjLBu7gx4Dl6sVVzMoOQ4wrGKMhezC4qMk7dU4+08pQYYVAIVAIFALrHgJlMKx7bTanxAyGKHwe0nlQczPw8O8VEDPyZoejnFLgKZdmG70S0mZi7klm6xF/ZasCSJiZYq4cZp4pazbI8sFGZiG5ASnPNOJSY4Y5RKlSPmXiQkSJ5k5jpv+4444bKGLikTcQKSffe4qgmVv+6owC/AwD+yWiiFFaKGzTXJKS/7Rjj1/iYyz0ONpnET97ChSFz9uM+ObbROucEcQ1BpGRduEuZLY2JFw9s2pgo6+Nqgy+vA1Kva1wILwUtp6ExT1Le8DC6g9FL/mGHy+XrlDyMMPtNbEww5M9FertmluWD6RZZWFM4GO4MV7ES59XarreY9kmbStNVhhcZ7ZbGzNqGJv6nbgYOPBz3ZP88qpP2JjF1veUm/EJK8TwgFNWDYSlPR3VI4q28+CibzEU5Au3Jd0KUdKFl0zEYIrhm71CVlvgZyWGrKz4cHtyfdBBB7W0cbXTnu6p4BeXL3tH3AvBsiVa9pfXr7pOX7Qi4P7ccccdG5tVH6tFVmHcy37eYJW3Xmkj9799KNpFXlYM3M9WhNRL+yBvt7KfY+w+1yKX/Y3vZ250jNkyGIJQHQuBQqAQWL8QmPt0Xr/qtkHUhksABRb1ihADwCxgr+xQqijVHvaUWL76lHiv76TsU8D9ogznY1GZET5+2VtvKHdmYSkeNnmecuZmTQqIV7RGGY6yFeWGAkyJDFHyKVJ5S9MPfvCDtlnXtx7ItnGXgkoOJcQbefBHgV+6dGnzU+fiQmniu57XiOJXH3n09U/ey3M0yzqWwX+fsSXcZt+82ckMNyzNiNu4zBBCwcA5lxhuIyEytEFmdYVbTaC4kWN1xqx09jB49Wxm+yODz3wUTkqijcGMyP9n7zvgrKqu9U3Pey8v5v3y8pJ/iiYxibFGTUBUBEQUBUOxgIhKkw5SlV4MCgIi0kRAVKIiiAgKKk2sIEjvMPTO9Jnb28z3X98+d8+cudwZBmTGGWbt+e17ztl9r/PdO+vbaxe7Y45VlJmeFg5LpKwsqcxSOaQyzn7xjAEqjNbRUkRLBMkRw1kGZc53RSWeBJQkgmdz0JFUkrjwmbigomoVeZIETpki+eSOSCQi27ZtM/l4tdOpTIB8cE2NncJDpZSLkzk1hu+dbeZUJjpLdGhhorPvjfKl5ztgGJ3bcsA1EsSamyi45WUyJHzwvVgLA6NIfvm9IWGhsm/bxDh+5ygnS9IZRrJA+VDB5vayxJN1XHvBHansKeU2nGsRSAbYF9t+4othxBwdpxVy7QR3GSP+SYA4/Y1kg4718jvEHc7oSLxIYGnVIunlu7QL0kk2SYLsmhOmZ93WETP2d4JhB+X76J6SZNPpVSWgElAJqAQuDAkoYajk77F27doFhIFdsf/Uqdhxao5Vlmw4FXqrMHIEmCOZ1lMBoaJgd1yhQkkFg84qvRw15/QDO2LMOFs2503bsxBsHsbRsz12xN0qZFT87Igk01MR4tkFHPW1yh3D6TgVhsoy09j6WB7THzlyxITZcCqNVKKoDNLZcPNwHj7s4mRO5bIypKypHLM/9HymzChLd/1sM2XsdkxrFV0qxxxVp7Py4jvgHHY6kiKr8PGZdTC/VSIZxvfJtiRzzGvTutvFd8/RcI5aW8d4+97ZJ9sehh0UBZEkwGKFeLDlMp67Ltk5+ZQRy7L1EQskiPQ2j71aksVyWQ7l4sYIscN20rvDqbySqFhn6yvpyrQcbbdYY31ub/MyzO1IGOwaFpuX/WWb3JYB218Sd0sIi0vPtKyH7aECn+goS3d/bTyVfDs9jrKz32XKnOl5tcSQeez32eZnuXyX9PZ7aeO41ocEhM7Kwsbx/bhxaKeWJWujzaNXlYBKQCWgEqi8ElDCUHnfnWk5R7d5MBr3wKeSmPiP3SotTMwRe6tUWcWF4TYPFRbeW8WBu6Bwm1A6Kh2MYz563ltlkfEkEdxXPnFklOmswsWrVV44is7R9jM55me/OArMKTA2f3H5mJbzqjnam2wNQ3H5zjacyhRHzt1yLKkMKwOmsXJm36y3eTnyzNFekjq7joOj0EyXzBUXzrTuOim3xLba95xYbmKb3PGMs+/fls+y7b07rfveluluL+/PlM9dRnH3dloV10DYPrrrO9O9LTcxHcNtmE3DKy1JnDLHRcNnaj/xaKcM2baxDOajZ/l09sopQBz5L40jsbbWxZLS2+8prYt2FzTW525PYn6SAVonbLsS493PJNAkbCQjJCjqVAIqAZWASuDCk4AShkr+Trl4kdMKOCXngEwP4j94eipxvCZTaBIVRZueouA9XbJ8Ntymsc/utBw9pqMyQm/b4M5jEsQ/OLJsFRemcXu3QmXz2PIYZ/to8zMNZcARXSp0VLiZpiwcR4JpUWHdlGdx/XPX7e6bO5x9YTm2HzxPwk5v4jkENpx5rKzd9dkwd5nue5uW7SxNW5meZSYr18bxasu1dbGdyfLYeF5tfncY75nPlsf7xPfmLtems2VwIbRdw2HLYZrSeFuGuw22fHd+dzoqxyTH9rwLm96dJvGe/bFts31JvCbmcT+zDpue4e46E2XlzmfvrQWHz7YcXu29TZd4ddfjjnNjktPgOC2O6yEsOXGn1XuVgEpAJaASqPwSUMJQid+h+5+27Qb/wRfnrYJQUnxxcWcKZ9lMQ2fvk+WxbSgpTbJ8pQljmYnO5ksM/ybPLNO6xHtbnzucad3hvE/Wf1tmsmtiebbMgrSFTSoIsjfJ8to4e7Xts8/FXZPJuLi05xJemrbacktKa/tzpqsti9eS0rrTncu9Ldvmtc+8lsbZ9KVJm5iGecv6vSXWqc8qAZWASkAlcGFJQAnDBfQ+rVJRFa98jSX1u6xeM+u0LrF+G16mV1ZPT65Eb5/lls4SE+fpm3+6+/vNSyu7EhLfRXHPJbXAnaekdKWJSya3ZGHFlWXbUly8hqsEVAIqAZWASqAsJaCEoSylW85lW6WiKl4p6pL6Xc6vonyrsyTBXuO1Ux7uqTBWPomNY3hp3dmkLW2ZZZHO9vVM15LqductKV15xNm2lEddWodKQCWgElAJqAQSJaCEIVEi+qwSuEAkQCWTzl4vkG5pN1QCKgGVgEpAJaASKGcJKGEoZ4FrdSoBlYBKQCWgElAJqARUAiqByiQBJQyV6W1pW1UCKgGVgEpAJaASUAmoBFQC5SwBJQzlLHCtTiWgElAJqARUAioBlYBKQCVQmSSghKEyvS1tq0pAJaASUAmoBFQCKgGVgEqgnCWghKGcBa7VqQRUAioBlYBKQCWgElAJqAQqkwSUMFSmt6VtVQmoBFQCKgGVgEpAJaASUAmUswSUMJSzwLU6lYBKQCWgElAJqARUAioBlUBlkoAShsr0trStKgGVgEpAJaASUAmoBFQCKoFyloAShnIWuFanElAJqARUAioBlYBKQCWgEqhMElDCUJnelrZVJVBJJKCnS1eSF6XNVAmoBFQCKgGVQCkkoIShFELSJCoBlcDZSUAJw9nJS1OrBFQCKgGVgEqgIktACUNFfjvaNpVAJZVAvrSbXp1KQCWgElAJqARUApVfAkoYKv871B6oBCqcBJQwVLhXog1SCagEVAIqAZXAOUtACcM5i04zqgRUAsVJQAlDcZLRcJWASkAloBJQCVQ+CShhqHzvTFusEqjwElDCUOFfkTZQJaASUAmoBFQCpZaAEoZSi0oTqgRUAioBlYBKQCWgElAJqASqngSUMFSSdx6JRJCamorjx4+rVxlUeAycOHEKJ0+eqvDt1O+T/p4oBhQDigHFgGLgzBhQwlAJCEMoFMKOHTuwd+9eHDx4UL3KoBJg4BD27z8gfr96lYFiQDGgGFAMKAYqOQaUMFRQwmD3sec1JyfHfNECgQCCwaB6lYFiQDGgGFAMKAYUA4oBxUC5YUAJQyUgDNnZ2UoY9Eeh3H4UzhcppWVMvcpAMaAYUAwoBhQDlR8DShiUMFQ6RfR8KbRajlqrFAOKAcWAYkAxoBhQDJwZA0oYlDAoYVDrxXnHAKfPqVcZKAYUA4oBxYBi4MLAgBIGJQznXVlUpn5mpq4yUhkpBhQDigHFgGJAMVBZMFAFCAOPkDrdFYYW3gHue+fJCeFnYVzhnTvN6XXYkHxXXht2pqt70XNp1zCQxXOeIK/lBcBAwei81B209Yakfnr+EAizlmthurP/cQi56giY8pwyS9/HwrawPTZfadtl07mvtn+BoL+gPFvuma6FfTjbfrhlx34wv+N5HxKZhwL07nTJ7/muHLmGpRx6KyN3+kJZnalP5yNe57hW/jmu+g71HSoGFAOKgQsTA+VKGPJEcbaqd55ozPSx+NWthBcq0zZV8lims+XlS2n8o4vGYsiT3YUYJk8mjOny5IPXaPzKumPyx1QMZ9poLGruGcecEfFME5MnJ73TbqYK5TFc0khmepZfWBbLzDe52A7mN/1nRcV5ibLubAkDv6DRaNQQBr/ff9akgfnPVumjAu0LUcH0IxLwIhbwIOoPI+IHwoF8BAMR+EM+SRMQL+XLc1AU2uLqIdHxen3SByddIBCWfrC8CGKi1IZDXgQjXnhCHnilXL8ovUk9FWbJZ7wowuFgFEE/25kDnz8bAeYN+eEPS35pW4B9kPaFWUfch9xKdFjaHI1IvT54w0IQ5NnnDSIclvZFc5HtZZlUwP2SX8KDEaO8236yXz6fz/Q72yfpw15khT3m6pN2BAOST95ZiITPeLafxC9o+mcJIHfLoszZ59xANjI9GQjnSdsiHinbI3ISPPoFmdL3sJTD9+L2pn1SV0R81O+BPzsXUj38nhh8njD8fod8+CUfPfvkC/B9FL4z9tn2S6/ElHqVgWJAMaAYUAxc+BgoB8LgKPFUhKknR0XDpo9IcFg8lXK3kl1EmWamEhzLY17Hi1KeHzPZmYVhMUkQy6ea7jhTt0QwzoZR5XfyO2ny5CEijWI828YrSUNUPkkSbHslyCELcvVJAkMsJDHrZB56uhD7K1cnP9togot+uDPEY0pLGNwFxYQoUaE7G8JgRwLOVRHkaHZElMooyYKQBksYQoE8UX6pXIriKQpuwIx+C6ExYcm/WFSqI+GIKOOisFJ5FSU/4BemLle/Lwe5sVNIix5DBtKQlZeBDH+6KLRUak/3zBcQ8kLSEAkJuSMJiWQhN3oKmXknJX8acmKZ8InC7xcFPiTKcUQUfeup9IdDJCmiLJNQhIPwilLui3qQmyfKeiwdOdKGnGgasoPZhoCQ0EQkbUQISkjyWtnyh5R943vx5PtxVNpwNE8OSck/jlS55oLtEDIgcgxKv+nZd7/pF+VHxT8AT64o+UEfsn3sRya80g5ppeAvU+rPQjQoFFVIQ57kDbEsSev2ofhzWEiPLyBkIyJ98kAITwSZlDkJmDAInyF5JFU+IQ1CZIQg8eBA+tzcXIMx/eeQHMMqF5WLYkAxoBhQDFyIGCgHwiBqtijEVMRlQL7AUUemom4V8AI9momNl0gGFkTIfYJjlFX2HfuCQw5E55TRdsfHJEGUicQxPe+ptJ9KAzw+Jz+b5WqaKHrA3v3A4eOF4Y7CLxYISSu6KA4fA/Yfkvuwk8b2g1WxfFoxwlIo6zQWCKkhIk/udExrPdO5XWkIA9MvWbIE/fv3x4ABA7BmzRqjpHJEmsqqHZkuCbhMQ89pT16vt1R5bHkRIQvwBcWyIIqyEAZnWgyVVefHgtNjIlTYzVVG8AMxiRPFXRRoprHpbHkmPD6aTeXZ8aLEikKfHU3FwdhWbPSuwienlmN/3i5Rs1OTkgWHQIjCLS8qLPWHRZH2i8Ug3X8MB0PbsD3yFXaHN+BQaCfSA4fFSpAp8pIRekljCYNz5TPL4Ki8T6wAHhxNT0GKZws+T/sIm32rcSJ0SEiDWBiiAVGkpYw48XATBvcI/bHwSWyJ7cCm2HpsiK7CxrzPsTrjE2zP3CKKuiN/+078Ui9H+IOiuAeDYsERhd0byEFWMA2p4cNISd2Grfu2INVzWLAlhE0YeEyITlTyhCQ98yR6r9SRHclFRn4qUk7tx66Uk9h86KCQMCFdMb9Ybrxx70EgIhYfebden9cQhaysLEMW3P1xvzu913+SigHFgGJAMaAYuDAxUC6EgYrt2jU78PSIV/DsqPkYO+Yj/GvEXPR9cgL1TaM0FyjMBTeSydxTlXcHsjTHMdRRuJ1JPwylFeHZUXMxduxcvPPOF8Za4KR2Pr/6ehfuqN8W11zbDC9O/cAQBau0M8We3adw+eV10eKR3rjrnm6ocVMPZOQ4eanshyRxx84TcXOtlrj/wX74+41tse+IsAZxbCnLoluzbj/GjX8X48cvL+ijY6koJBgsj5753HnlUTiT02dei1vDwHRPPPEEatWqhYsuughPPvmkUegsUbCKHa+crkTPLzKtCTaOaVevXo1HH30UqampZhScI+Gl+cJzDnzYWBikfJICGRmPyAuN+ERJl2lEYSEHJA2cDmQUdyrv8sw89G7CwL6wHe3atUOHDh3w4YcfSXtjhsB4RPHNCaej/4gO6DigFdoN64g7ut6C11dOF4WaSvXpFgaGc5Q+KiPuoaB4Uan/9VJ/3N/jHrQe/DDaDHgULbs+iE0714u1S9oko+hhsUKEaFmIe4c0iLVARvhDnHokyv7Uuc+jUYd66PFsBzTv0wg9xrdHqlg+ckSRj8gIPgkDZUvLBD3vzfvgfSSMLYc249YWt6DN4HZ4WNpx79B/on6n2nhv9duioEub4wSOVxIGP5V/KZPfAa47yBHLQEradrQd8hAe7dcc/Ub1Rad+rbB01UJ4aEGgRUCmXoXEGlJAGoQEWOJAQpAlBOfD7QvRvMcD6Nt/MB7p3wZPvfYvpPnShCyIFUUIWlDIAt0T/fqiY6eOmD17dgFmLHZKgxFNc2H+49D3qu9VMaAYUAxULQyUA2GgKgxsWL8TL7zwhijzC1GnVj9MmLAC/3r6NaRnFU4jMgnjH+kZzk3Eye6OKnJPtdpZreDYGPh8yW8bYuDA6fj0051FpgBRmT94OA2bt57CmLEfYeq0FQUj/o56Dmzbvg8fr9xYUEe9O0Zg3IT3C5637vTjllv74OBxqvrA8GeW4L4Hh5h7py0Ovdmy7TjeeHMNqlXrJtYKMWWII2FwexMoH2wXLRLsqm1HaQgDFXvrOnfujMcff9wo+lQ2OQXGKp9Ms2/fPhw5csQkP3bsmFh88uDxyHwUcV999RV+8IMfmBOlTYB8MJ75S/pBCAVkXYYQvpJcnjQxKOSBi2pJHhyCkZwwDB061PdIVEkAACAASURBVBCfadOm4csvV8kUmKi0QZRomTqT4UnFik/eQarvqEzh8eHZ9wfj/r4N4BUZnE4YGCaj9UJgYv48qVuIgPyNmjMQXZ5ri8M4iD2e3dh1apdMBRIlW8gC1yy4PdcyOIRByIYo7L5wlrynIHo+1Rmf7VguXY5id85m3P1ELSxcM1/enfyJQk/CEJC1ESGZmmQJA9dHBMTzuvd4Ct6Vfpz0pONI6ASWH1+KbqMfE4vBIWcKUJwwcDoSCQOtLHzPzpQmHzKDqXj709fRekRziH0AMskJr7w/GX2e7oLjWSfgCcv0qHCG9FnWJ8SJgnOlBcgrdXhxIHU/ek1uj3+92h9pmWlYeeAjNOx9Oz5b94msjch1iItMW2KfRj77DK67/jo0a9YMnPJGPChhqFr/JEr6DdA4xYJiQDGgGKgaGCgHwmBVYEetPHYsH/c1dRRshlCBloFdTJj4ER55dBaGjViJe5oOx50Nh6Ftx0lGgbZTipwSkn+SNNBxOtDf/tYOK1bsNM8MNYuP88Oi/hS25YUJyzBxioxiSzwVdpOuMNrk5cfNNXvhuQnvFDwvWLQNrdq8aJ5pV9ixB6hzRz8cPOqU41b6mej2eoOQsjdOGKR8Tk8KSoUy6I2x4z9Hj75vFbTBtoP5SkMY+CWlIknlnhaCnj17GmWOij6tCJxixGkkv//97/GTn/wEF198Ma677jo8+OCDrMK4Bg0a4NJLL8X3v/99XH/99UJwquHOO+/E5s2bCywSxf0YiP6M9E3AtHZbseCxED5qE8L77SKY91gU77SPYGqbDUCWqNZCGrjomesXjMWBSmcSC8Ozzz5rCAMbRrJARdlMS5KR85BM+QnEPMiQOf8BmYw0ceUoPPBE42IJg1cUZo7OkzCEw5xKFsa/5vRGx6kPiaK9DZvCXyEdx5AZPiUWIBmRF+U8LKQmIu3kNCTHO6QhJFObvLleI9P9hw7AL23JDmULbclBg6G34cX3JhtZOlOBxCoghMGse5B+WmsOr7TweIVQeKKyNkNAT7vYM+8OQ/8XesldyLTXkjy/kCu/yIiEiWQrwGeRR0YoFbNWzMDjL7bHEezFKenDZ3uW4LEBLbEvdR9yZD2DJ5wm8s6JT2WipcHxXBjN+z37hOh0vAHrjgv+Iz6cFOIx9PXumLPoTWMp8YulIyRMMCjtDEpfHu/RHS1atDCEgWRBCUPV+OdQ3Pdew/X9KwYUA4qBqoeBMiQMVH+pPlMldzRxKvOHD0fR7P7hRsEyo+2iyNOJPoXW7WaiYaNBZo3A6jUZuKFaS+yPK+Im0Rk+wjLlg7VefW1bLFm6zaR2K+ERNiDupk77FC9MWmIIi03D2AAXd8rN63M+R936fdG67Wsmh2NPALbv9uCmWzvKVBan3QOHL0LNun2x5GNpqDgujLaOs4ruajgcKXELA60I9HRvL1iPWvW64ubaXTFo6BQn0PX5TQkDlVO6X//612jYsGFByY0bN5YpV5cXPJM81KlTB9/97ncNUfjnP/+J1q1bY8+ePWaRa0k/CqK5I7hfrCyNFmNGs314/b59eOX+Q5ja7Aim3JuCsS2WQswBMl2JhIFfLo7kC1mQkfjiCAOJCx2tH47yLKTBLzstyfqBYH5IrALb8eigB9BoYF2sOv5xEusCpyfJuLsoxrxGDWEg0oCRswejxaDGaNFPfJ+GeFD83vBmZAaOC1kQwiDKcFHPRc+CKZlalSeLVTjFikQg3SdrJ2TW/+RFz6LZwLtxKnJYpvBw4Td3E6I1QhRuwaIlC+wHFwyHZXENCYDfL9YPqU8mOeHe4Y2xas+XgjkhSCIfnyEKDkEwO0rJtKqAWDt8jPMFZHelDGw8uQb3D2+A3q+2x/RlY9Bm6H1458t/QyZuCWHIkJ2cMqScHClPphYJQQlzmpKsg8iVNvrEZ+SexNCXemDYK48L3diJRfteRv3uN2DmnGkit1whs2LdYNr4oufuj3c3JJOYsn0qCRcaV/X+keg713euGFAMKAYubAyUMWGgosY5KyQODm04cDCGZg88bZ6pqMskB3NP/faeJgNk5NU8mo/OXZ7Gv+esLwwo6S6uiPNylSEMO0xqcgTW4yYFjJgwcRkmvbhCxp2dOIaFZOtMppOdKfHJ6n3oN3guqt04GIs/2Mto0wuSiV5PvCCkoQsaNH4ajZuNQYOmw7B2s7PQgWp6vCkmT626T2J3ijP1h22xPjU7in5DJ+GxLmNw5Pjp83rOhTD06tXLjP5yBJiKHR0JAK0LkydPxoIFC7Bp0ya8/vrrJo7WCboNGzYY6wPXMFhHBZcWCl6pvCf7IeB0o+hJIHO1KPgfi1VAfHCl3H8C5Mi9Z52UJoQhIlus+kSRZhkkC1xEzG0/E9cwuC0MdqTdXM2iW+4IFMH+tH2YNHc87h96N/pN7YFc2ebHK+VxWhG3R81hW0VZ57arAQkjX/X5hHTk+bDx6Fp8tnm5NEosHTI2P3xqdzQdVlveq5ALbo0q5XAqkR1Fpwy5tiHmFYU/S3ZSEuXdH/OJ0SQVU5aPRKOeNfHp5gVSVobkkdF7Dy0ComwLQ+KOQ5zCQ/k5fWHfpTyxEoRlx6eoUI73ZSpTE1nD4JX7mDTVL2Ynv+ywFJArt4Lluo8o133IvDyf5OWOT9myG9I+3y50eakNWo5ugMfH34snJ7fD/FWzkBE5JqRAyEI4VxYq08IgVhligbssyVSkVAnPFusB7S2f71iJzmMexV0DqqH5s7fioeG34+0PZps1DAEhDNx9iQu5fWLd6dGzRwFhsLJJhgcNu7D/Wej71ferGFAMKAaqLgbKkDBY1ZMqNNVwxx04GMUDLsLAswvo5PgDIQz9cbJQZ0XbxwZjzrubnQTJPpnX7eWRNV15bTssWeZMSeKz28erw4RJSzHxxSUuwlDYRslS4AYOXIiWjwwueLY3H763EosWbcXMN/ej0QMDjaWCtIje1sG0ter1F8Lg5a1zToNERrllVIIT3bKIO1vC8Mgjj4CEwY4AU1GlckfHqUo33HADLr30UjPlh9OSjh8/bqbIcG//5cuX46c//Sn27t1rlHrm5TQn5qeyy2uyHwnRlJG63Y9GV3ZCh+qj0O0fI9Gp2hi0q/48Wv1jNJpc1x2yAZHZ7pP7+pvFwxzJLwVhcKYjOTs4mXMKhACYxbxy5gDd0pQlqN/2rgLCQMWY7WTbrSNh8ImST6uG1yMKdFRG3PPlHAfZXlVOicDHW99F0wE1xFBySpRq7lAki5YjQhBiThl5eVwoLtOSuJhbpgd5xDIgm7li2soXUbv9jZj+wQSj+OfKgmxvKFMW2JO4yG5KNKnEHdtDwuXIkPKUcsT6Iao/BkzognFvDpbdtLLFtCX7cIk36z1kzYdUXejCAhrOYZO5bJ5oFiYvnIDHRrbDoWiK9OIU5i99GV37PYSDp7bKdKQsM+0pGCeDLCZfvlwBj0yhkv7l0lojRIJu58GNePn9sXh74yRZE9EQH3+11FgYaF1wrAzOWpCevZQwJMO/hlXdf5z67vXdKwYUA1UNA2VMGKg6OyPdRkORjzRZzNy0+fP2URSuQnd3k2fM6L4Na9NhDBYscRbqWgW6MLXcsXi3l0eq4lcIYVi6fJfcOdGWMLhmJGHKtA14cWbh4mbq67RyiJGhiHtywDto2aqfCWM5AdnT3+3q/XMQBo2YboJsU9yM4dZ6A4QwOCP5ciSE2TGWiQ/JtqyDhs9D+86vYPsO0aoTnO0vr8XtkkRl3jruLDRw4ED7WKA4c7rRrFmzTHhmZibS0tIMaRg+fLgJoyLLrVm/853v4OhRZ1oVI0gkqLQznpaIZF+MqGyTSl13/+pUpK2LIGdDHjJl2UKaiPWkGIaObJT2ifEkILsm8cAxMx1JFObidkkaPXp0wRoGN2HwyZatWf6TssD3hBCyTFHw0/H+9rdxZ+t6yIlbGGhdiMSnYf3ukt/h2huuw7qNG+T8BrE6yDoOv0y1kRMeJL+cYyATcfLk85Wl49C4xy1yLwuEpQ5OFYpGQ1i7djX+9Kc/onbtW2U70WzZzlTIiOwc5MvPxVtr/o0mT9fHqxunyASgEzgc2YFj/hT48uQsBBIBSZvjyQXle/nlf8Ebb7xh5OxYK2RqkUxLypK1AZsy1qL1oPuw48gqIWdemfIkO01xdynxefKV2bFtN+5rdB/qVK+Jg5t3ivlL0OXhlK4sTJg1ShZwjzBrMHJlCfemw5/hke73IuXYdiEMsnZD3pkAADMmvyi7edVGq5YPSRvyZPcqn5CXXORKO7kehKQlX+Q5d9UkPNCjLvYe3SVkQ/oppIfeL1OruK1qz1491cIg+E32HdAwlYtiQDGgGFAMVAUMlCFhoHpNsuCMCK/+4ij+NWQ5evRZitr/nIyeQz5G5ydmya4vTqoFHx5D9brj0XPwHFFtgM+/9uO2BiPQrP2r2LQjXUKSOKuh26skoeJ/1fXt8eGS7SYDy6Kz1wWLdqLfkJV4oNVcNHn4LXTv/xnmfeikZbrb6z+JJve+jucnH0S3vh+hRp0BWLhkLaNMb3xSwQbhIq/M3o+6DQaieevBJq7gg22xlcltEcIgcSQNdAveO4hatz2FW+uMwbBhzhQht+GhJMJAomCnHHExKnewueSSS/DnP/8ZTZo0wcMPP4xdu6SR4n70ox+ZKUlcu0DicNddd+EXv/iFmZpEpZz+66+/Nor6TTfdBFoqfvazn5nnlStXFksWnC8Ht/GUvfk5Mi9EwPEyBUbm+svMF/H5ck+yICc+yxSboIygc2elsPGi/Eoe+yVjW0eOHFlAGJxpPI6FwS8K9bzP/o07+16Hvm+2wKC3H0Wz4bdi0ORucpaGnL4sfeCUJ4p+tZxFwS1mmz3aHFkyqh70cKtUKUdIwRNTu6HL9JYY/Vkv9JvTHI36VMPSjbIdqcz556Jn7oaUJ2sJ+vTtZcqYNetVUbBJnGTnoWgGjnh34r6hdXHXmH/goWkN8dirTdF4ZDUMmN5JyIhYEaRfHjkEbcPWHfj5L35pyiDZ47vi/H9aG3JlMXe6AGTK0mlo2rORbNWailw5iC0k06ZkAY0s0hbGKhib8eLL+PFF38cfLv4FRSOLx+V7lCOWKmlPyvbVqN/jJgxc2BnT1gzH/UMaYOL7U3BKyEIuF1zLNCK6Fo0amTYMka13jeN0KZl6xXUQ27M3Yu76mRjwSns82KseFnz8qvRRpjKJJccrax7ow3nSK1k70qt3LyUMShgKvqv2O6vXwt8vlYXKQjGgGLjQMVDGhIHqO71MIfloLR5rM0TOMBiJzj1Go22nIWj+UMeCrTwXLvgMnXqMQZfHh5j0H3zwJR7rOAiP9xuDrTv2m7DTPqghJng+Xn1deyz/eI9JLhvkFHHvvLMcrVo9KW0YiY6Pj0L7bqOwYNFyk0bWt8qUEaBtu2fQpsNItGg1GFt2yxC6uFBcm085mIpG97XDQ6374qVXFjpx0kVnapXUzga4CMPNtfti7z7HEmAtDPEjFjB6/Bx07/2iKYNTstyuJMLAUX9LGGrUqIHq1asXeO50dNttt5mtUlle06ZN0UgUR6a57LLLzC5Jhw/LQV+ivNrpMky3ceNG3Hrrrbj22mvNOQh20TTrKf5LwB18ZHReFFRON+JC3oDcc+tOWhS4WJcHpjmeW6uK8i5KsXMmw+mEYdSoUUbBZXvYR2tlCPJgOJnpP3PxVAyd3B/9xvTCa4umSojM1yfpoSLMFyfu6r9dix//139izjtvy9QgTvORqVWyYJjH5n255VM8NWUw+o3vie4jHsPydYtEwU4XhV1OL5Zdi7i4mqSBhOOyy/4gU7T2mP5wLYA/JOcxy8Fvo6cOxWDZ1WjAlL7oP7E3Rkzph027VstrF+uAkCO+x/cXf2jKeO655806BlpoHDlyepP0X9Y6LFv5AebOfx1RUcz9MmUpygNJcoLIE8/DPvr26mvKOL7nAKJescp4ZVpYhsSRUMiUoRUbP0L/SX1k8XJvzPxgqtAVUfZlIYRX+hGU/DRl1RJs/Oh7PzRykY4gmCMLmkWWadmn8NqcGRgwogeefv4J7D0mZ1HIygy/HDznnPIs71UsLTz1OTs3C506dzK7JBETfC/0xWNC/2mobBQDigHFgGJAMXChYaCMCQO15zO4fFH08h1SYVPmyb77ic4q0InhiYSB8X+7vrVMs9lpkvKkZyrzETkEzK6XOK0MBuSLIlaM40JnehcPKJKS5Ro+YRhBPEoSx4SA1Lm9N1L2OFYWSxiKZJYHtjHR2f7ymjglySptVKiLc1yDwEXLyRzLZJxVZFleoqOCaxc92/pOB78zmh2MkwUqmDyt2CfKtXPlyL8onkIaSB6C9KJUO9urOlOUbJms/5mRzxQQBq8o2ZYIhGUNARdJy6kPrmaKii5KLclAUJRhnrlAR2X/8iuuMPc8bTkic/8jwho5HSqWMN+MpXE0nu0KkMhw4bRYS1jGsGFDTRmmb1K+X8hErlfm0xVpg0kiL1AOVZMdjLgVq8/rw7hx400ZGzZsMqTH6SPLlulGXgFFtuCbBJFEk1OR6IUQIFe8TPM6eeQ4rr7qavzhd5eaCnxero2Qc0Yka0wOogvLNKyoWELoZGNdaZG8K2Md4GLrqJAUYPnS5aYNQwcOMekiYsGISfsMKZKpRg6zNVGCXU49kilV8u78JHzyPrnegS41PRVdO3bCI81bCME8nTCQGNp3qFeVhWJAMaAYUAwoBi5MDJQhYXCUkZI/RdO2WrQosfJkXL4NKzmzxDJHXInkbbyASy+9FTVvbonePZ81yhPLy6d2Zisw5Up9pk4baK9OOfaJV+tZkw1nEXmS3zrXrQl6dfoiNLizA6688m6kpcYJkS1IUthbe7Xl2GsywlCaL6FdpEwln4QiMU8yi4Gd/sP07jwMT8x/+nPRNAFO/ynwtDLwi8MR6ThhKLgW/UKx38+/8IJRcv/74p9ilKxnoGx4KJttB8tlWVRceW+IjCEgUr4sbqYbPGgI3ntvkbl30svIP+tnXzjKLu1hPh6ixnsnjdNG9p0kiQfgcQF4TMwFTn+p7LNuliH1UvHmVQgGy+RWrCQs5l7WKCxbugLjn58gZYnFRdI5eZnWIUu0RPA8igDfj8Sb06+FNEToxQqTlZEt07NG4fNPPhWCEF/zIeVG5UCSgJRpF2FzGpXdojVAK4jpj5QhBGm/HNTXSda1+MR6QSJjDszju5D6nD7ZvlCO7D/bWYgXWp9IKH/xi/817+TxFq2NTEPSDveWuE6djlydcvVe5aAYUAwoBhQDioELDQPfMmEwOsj5+6CGGXei/yDP6ulWm3fF23SlvRan2BeXn0YT0eHMFBXynyJMI/5YUpnfhDAQpEYppoJYITyV80R/etvM+QmipGblZBc5kI2WBnc/CvomSrejfIsCLsq2X7Y/5dkFfirvInxLGKicOwfGsQ3Fy8Yq91SUHSX/9Da625F4TzLGXZD8ouTz6vTZXYZbBk446yEBMQRCrBQOkZBdnYS4hKWtXBdi13qYfhtri5AIc5XypC4rW2camFOuQ2K4M5Xkd/nENttn23f7zOlH9CY8U6YyZciUp1yZWiWEzy5aZ1olDO73q/cWP3pVLCgGFAOKgQsLAxcWYYhr70ZBd2nyli+4gsrl1tab2J7SVH6uhKGyfkGp7JIwRGQ+Dc/DoGXB+tIQhqCsAYiERMGVK5V1ryzWDcgUKVo2nClQznSo05X4wi90otJ8brIkKaA1xSEnpSnDEhoSBCr3zENywPa4LT7usswov6nDWm6K1sd8tBLYstx5S3PPutkGbgnL6Xw8aTosso3S4iHTm0hY2FYlDIX4KY1cNY3KSzGgGFAMKAYqIwYuTMJgNfW4Zu4o3xzmp8khPoWpNFr7N0zDZnBtA69uX5piqyRhELMQdzziFqnc9agkwkBlliPzbguDzyOHkskhZyQMPjlXwePlYmbuzOQsSOa1JEWeSvI3/RLzcDZnTcS5/yCyb1bZTzaFrLCN7vUhRQkD09BCwGvJZRRtp9tKQVJCYhATspAnZCFfLDh5YgWJxq0cJAzOlLOiZRS2T8NVFooBxYBiQDGgGLgQMHABEAZO7El0yUgBw+iTpU/Mf36eLW+x17MptbwIA5XT8gfy6XU6FgZnHj5HrU8nDMzjeC5mNt5FGIJmSpJMwRFS4JGFxx456dgjux/54paHQtJwet3nt/8sn6Th7H8gLWExZKgU78XITGQQiMvlXOpMzFOEMJBsCGmgVSEmRCEm6yfyeC+eU6UYl5hfn1UmigHFgGJAMaAYuPAwUMkJAwmAbB1zGgkoP1JQEgmwSn9JaYqLs3l5tbsklcUXsLTK6fmrO7lCXTJh4BfPTr0hWeAp1jxfQcKEKHD9Ai0NYVkwTM9F0c5uP84OSFzbYOIljbOWoWy+yJwGRCLDxc3nIi8SBjdpOFMZJFZescbweqa05yveEAghCpY0nK9ytZzye4cqa5W1YkAxoBhQDJwtBio5YSAxSGZNKE4NrzzhZyIMVrEs7oW7lU+e4HzgwAFRZouOrjsKrijcrnDmK27evK0rse7iprzYdCzfjlxzNNzZYpXTWWSXH1lnEBEFO+qX6TN+2SBUthXlbkEhefbKNZe7/4iCSguB9TwzwXhDGETJlikyfkmXG8nGqdhhfLR9PibOG49xLz+HE6nHRIGXqUly/oAzfYky4NQjrm9w+5KmIzEueTz7aEkXF0vbeyurs7laGZU2D9N/G2sIzFQl8070B7e070rTKVYUA4oBxYBioDJjoJIThspDAM62paUlDFTWrWMe66n0x2QBMcHZu3dvcxgb4yxJYLhVcHnPtNYxDXfp4ZXnOTAf59RTGbZXxjEfFWaG0VvHPPRMb+uzyq1fCINzLgN/OEQJlxFyOYFNziCIe3svR1fI0QKISbGh+InR1koQkbMG6LljD7cm9coZCR5J7JMzlEfPHYy7e9yCCQvHYebCl3Hg2F7Z/jRHyEYOopI+QgtAEaLgJg3F/ZjZNKfHW1JEWdi+8v5cPNduJC7wPpdyNM+5yV/lpnJTDCgGFAOKAcVAcgwoYbBabgW7Ukmn4zXZlCQqqlT46Wg9ePXVV7Fu3TqcOHHCnCHABa/WdenSBT169LCP5mpHwnNzqanLWWLZ2Zg2bRo2bdpknvnBNHSMsy4rK8vemsW07nqWLl2KefPmISMjw7SBbbSeX0COhhcSBrESyGFpeWJJAM8R49l2ljTkxO8ZTj4kcaGAEIS4N4exyYFsIZl+FJA2euSwMa+cVDxn3SQ06lYHB3NTIPYGBPK9yPRlwxf2igLvRZ60Jyr+fBIG9w+Lmzy4w0t1L2SBhIHEqlTpNZ3KSTGgGFAMKAYUA4qBcsKAEgbRRyuiOxNh4Gg23Q033IDvfe97uO666/C///u/+M53voMGDRqYuA8++AA/+MEPzMFbDOf9d7/7XdSpU8fEkxBQOa1Xr55Jc/nll+PHP/4x/u///g+rVq0yaX7961/jhz/8IS677DL813/9lymfZQwfPtyQAVomli1bZvJfIScs//WvfzX311xzDfbs2VNkhx5nyg3rpJXBmebD9QfL/r0eXeqOxcC738TQBnMwrMGbGNJwNp64ezqGtpxh2mHJAq+FhCFsyskVQiDUAL1nPIShsx/H/vxdWJf+KY7H9iMnkoPcsJwhEPKIRcKHaJgKOdc2WKuB+1qcsm7TFBf/zcOtBUYJwzeXpRIulaFiQDGgGFAMKAbOLwaUMBh1tOJ9lEQY7PQfKvwXXXQR1q5dW9CBJk2aoGvXruY5NTUVixYtwl133YX69etj5cqVWLJkCdavX18wBalbt274j//4Dxw7dqygjFq1auHqq6/G4cOHTdif/vQn/Od//qchBiQq48aNM/W+9dZbhhA8+uijYL3Wvf/++6a+Q4cOGSuFe+TdnjngFwXeJz4gU6pObgnjnafXY8WYU/jk2Qx8NjoDy0Yex6JndmLvB2LdECNEMgsDt0z1B+SQtfwg9ubuQrvx9+CxSffhwVGNcdegGug+qTUy89KQHkiDV0iFLyTTrIolCyQFxX25KiZhcMu1+LYX1ycNV5kpBhQDigHFgGJAMVA6DChhsFpuBbuWRBhIFCxpuOqqq4zy/vDDD4NTj5577jkzss+pQlzfwIO3OnfubNYw2C4yjsom3U9/+lP85je/Qb9+/dCmTRu0a9cODRs2NGV+8cUXZl4+rQy0KNDZKUitW7dG7dq1TR2chkTiUqNGDZA8sCySE6a1Vgz7hbSEgQueg2yDrFHYtyQPnz0bwZpRwLqRwAbxG8cAq57Nx45ZMjVLpiUlIwxRsTYgki9WgxgOZBxAq7H34/Hn2yAkaxm2pX2FZr0b4MNd88z0JK6XyA3LeodQcdaFC5EwONYcux1t4bXkHwdzKFyR07EdS5R9h3otWX4qH5WPYkAxoBhQDFxoGFDCYNTgivdRWsLw1VdfYeHChejVqxe6d+9uphzRokBnlfWOHTuCCj6nDzGMC5Kto3XhL3/5C7788kvMnTsX7777LhYvXmzWQ3AtAokFCcXQoUNNFrtu4sknn0S1atVMeZmZmXjnnXcwduxY9OzZEzfeeKMhEGwbvzBFR8JlByRRRgOiwPMak12RNn9wEoPuexNjH12BcY9+gvGtPsXzrVfimZbv4o3hXxhSEZZFziFZ80BPywKfo1z8zAPFovk4mnkYLUc0wXubZ8uSiAwhDdkY+vIT6DaurWy6K3XKNCiP7KTkM6c/W4tB4rW4Hzibrrj48xPuTNkqfVlF5VpcvmSkobi0TvjphKHk9Bfaj6L2R9+3YkAxoBhQDCgGimJACYPVnCvYNRlhsAqiVfqp0HNkf+vWrQWtp8L/85//HOnp6UaZZx4ShhYtWhjCwClFnMI0f/58k4dTif74xz8aSwTLZb27d+/G4MGDsX//fpOHFobf/va3ZiEzLRtc27jb3AAAIABJREFU3Mx6Z86caSwQDz74IJo1a1awS1BKSoqZ5jRnzhxDFpjHtr24LyDji/POyDh3N6IvHO0OySLhkJCAoFgOZANWDJzREe2fewgncQLrYqvRbuyjePXDl2VGUyTJdCNLAtzXol+OwrbaNMXFnx7OvlDWhWWcnkbjVCaKAcWAYkAxoBhQDFQGDChhKFC1K9ZNSYSBW55yuhF3OKLiTk+l/qabbjL3AwcONJ2hNYCKK6cH2XT2OmLECJOfCX/1q1+Z+D/84Q8F6UgkeH4D819yySWmfC6GZn4ueubUJa6RYDynQ9lyuVbi4osvBtc9cNHz+VOa7Uh54Q9LSKwXEbFUBGSakcRibcoq9BjZCQ/0boTmTzZFm0GPymJo2S0pIqRCrBlFv5CWBLivhWUnT1tc/Onh50IYmIe+aN2nl63xKhPFgGJAMaAYUAwoBsoTA0oYKhZPKGhNSYSBSiUJA0fuR48ebaYDDRgwwEwbevPNN00ZJBNW+WRZ27dvB0kCPbdhpaNFgaSC8ePHjwenGT311FMFOyQxnu7Pf/4zuMA5JycHEyZMKFhkzTYwDXdUmjp1KiZNmgSSlTFjxpitVZmX5ZcVoEMih0iAh7/JtqpiZaDbc3QXZn/4Cl6ePw2nfCfN7kg+OafBnApdZFGzmyjY++J+fM4Uf3o+yv78kaXTyy8rmWq5KmvFgGJAMaAYUAwoBhIxoITBqJkV7+NMhIEvkkopnU1re2GJgn3ZVOrdB7PZRc+Mp1JLxd/tSETsegdOe+IaBq5N2Lx5s0mWuJjZLoR2l8EyE9th23O+rrQwhOXEYXO+g/SR5zpEIrK2IV9Oi47JmgcSGpnCVHjCs/sHwJIA99Ud7763adxhZ74v6/6fLzlqOWd+lyojlZFiQDGgGFAMVGUMKGFwa7kV6N6SAF7twW1WAbXX8wHc4spiOJ09x8FOOaL1gI51k4icjzacexlcQM31Cc50pQAPcitY5+CE2V2Z3GsfnPosCXBfi/sxtGmKi9fwc3+HKjuVnWJAMaAYUAwoBio6BpQwGPW34n2URBjOJ6iKIwysg1uyJnMVZ6qNLIKWXZYcC0JQph/xILfSkhhLAtzX4n6wuK6A6YqL13CVjWJAMaAYUAwoBhQDFy4GlDAk04grQFh5EQb75U5GHDg1iesWmIbWBFo6mI731tv8387VsSI4dcuCYbEuBOKEgdu2+kXJt57Pp7cxWdiF+2U/vf/aV5WJYkAxoBhQDCgGFANnxoAShgpADpI1obwJw5m+LJYgVBzrghvcVPzpCwkECQIPhyv0ycmB7RevZ5KBxrtlrveKB8WAYkAxoBhQDFQVDChhSKatV4CwikYYLsQvBEkCF2fTs3/JrCwXYr+1T/oPTjGgGFAMKAYUA4qBs8GAEoYKQA6SNUEJQ9l+kWkp4XkWdCQK3Ib2bL445yOt27pxNhaOxHzl8Xw++qtllC2mVb4qX8WAYkAxoBgoKwwoYUimrVewMCqz+/btK9iViCPi5aEkXqh1kCBwQfepU6fMm16xYoW5kkSUd58Tv9ilqT8xT3k8l6ZdmqZwbY/KQmWhGFAMKAYUAxcSBpQwVDBykKw5HAnnYWtchEyywKv6c5cBz5jggXKWMPCka3vGhMr13OWqslPZKQYUA4oBxYBi4MLEgBKGZBp6BQsjQ925cyd27dplLA27d+/Gnj171J+jDCjHHTt2YM2aNWZaEs+YuP7667F69WqV6TnKVPGo30fFgGJAMaAYUAxcuBhQwlDByEFJzeHUpMzMTLPVKbc7VX92MuA0JFoWOPqRlZWFo0ePmvUL9lC6Sy+9FFu2bEFqaipOnjxp5EuZW6/yPjt5q7xUXooBxYBiQDGgGLgwMKCEoSQNXeMuaAlw7j8dCcMvf/lLc73sssuQkZFR0G+7+LwgQG9UAioBlYBKQCWgElAJVDEJKGGoYi+8qnY3UfHPy8szlgMudCZh+N73vocf/vCH5v7yyy8305Uoq2g0anxVlZv2WyWgElAJqARUAioBlYASBsVAlZQApyXx5GpOTSJhuOaaa8z1xIkThkhQKFwcTU9yQa9OJaASUAmoBFQCKgGVQFWUgBKGqvjWtc+gxYGEgRaEbt26GYlUr14d3bt3N1OSDh48aLZY5a5UJA2JFgoVoUpAJaASUAmoBFQCKoGqIgElDFXlTWs/i0iARIELyEkGaGUgIejVq5exMjAh1zHY6UhqYSgiOn1QCagEVAIqAZWASqCKSUAJQxV74dpdRwIkA1y/wIXPx48fN+SBFgeuZaCVgY5EwVoX1MLgyE0/VQIqAZWASkAloBKoehJQwlD13rn2WCRAIsDpRjz1mVutcts3upSUFBw5csTck1RYp4TBSkKvKgGVgEpAJaASUAlUNQkoYahqb1z7W0QCJALW8/wFkgV6O01JiUIRcemDSkAloBJQCagEVAJVUAJKGKrgS6/qXbYEwS0HhnF60qlTp8z6Be6ixDC3lcGdXu9VAioBlYBKQCWgElAJVBUJKGGoKm9a+6kSUAmoBFQCKgGVgEpAJaASOAcJKGE4B6F9m1l0isy5S99aFpJd7U5IXNtg7226c69Rc6oEVAIqAZWASkAloBKo/BJQwlAJ3iEVWG7zeeDAARw6dAj79+9Xfw4yoPxK8gfl7AXKd+/evTh8+LC55zM986ncFXeKAcWAYkAxoBhQDFRFDChhqOCEgaPcXq8XmzdvNvPruTBXffnJIC0tTeWtmFMMKAYUA4oBxYBioEpjQAlDJSAMubm5ZoSb02W4MDcUCqkvZxmo3BVz+r1TDCgGFAOKAcVAVcWAEoZKQBh4RsC+ffsMWaDiql5loBhQDCgGFAOKAcWAYkAxUF4YUMJQCQgDTyB2EwYeNqZeZaAYUAwoBhQDigHFgGJAMVAeGFDCUAkJQ3mxSa1HRy4UA4oBxYBiQDGgGFAMKAbKgTDkiUoei3ve55ehis7yk3nWeZb12iz2alp9ehmnh8S7Z/OZBPywfXdHJN7H87ouXPScaGGoWF/cUHyKVMC5BuQ5EJZ7G65fsor1vvR96PtQDCgGFAOKAcWAYuDsMFAOhCEq6m9QvF98SDyf48rzmfVlSXs2LiKJrQ/LPT3rI2FhnXGXWC+fEx3DmIVZTTw/WJa4eHqbJP7oxJlIychA600hbJdtBwtO5uNFuC4kDFlZWWZLz4oHbpICkgOSBT9CgSDCgYhcuTi78hAGa8rz+Xygr3hyPrsvtbZf5aUYUAwoBhQDigHFwPnEQDkQBmq/VrWOK8n5VKglzB3M+2/sWIgtyBZulXQbHk9ik7qvpv54gA3Pkxu2taBcJuKz4wrv+MynRCLA+m0bGJf47E4v0QmuwhMGIQgBIQuBkAd+8bx3SETlIQz8QpE0kCzwej6/YFqW/mArBhQDigHFgGJAMVDZMVCGhKGoKl2gBxuiIHGJunUxyQvyleLG6PWnpWPB1rsikwQ5sVaBj2djoGmb+XCSkBS4H+OhDlmwBVty4LKomEwXGmGIwhfywhPORE4kHZ5IDrwhIRDG6lB+PxDnU9HnlmklfbHPZ10l1aNx5YcflbXKWjGgGFAMKAYUA8VjoAwJg9WiHQU6X6wKPLG4wHHk3jhe7bSheFCpLyyPU32cslhHfn5Mnhju1OUmESY+oWyndVTio4jFQpKX05jyEGVQ3DllSEonsQ0uuBYYTEz9TrBNWnjNj2dniG1f4rWgyIKbimxhCHE6kl8sDPleaW9EJOgT6QWRGcoWawMtDcUD75vEUaFPVNoZlugS0ySr000OeB8Ohwu8O86dlzh2P+t92bxnlavKVTGgGFAMKAYUAxUDA+VAGNyat6PSRUUnjwpHIGeIiM7MFEInRKGmMn02jgp3fF2B3JEsGBcvJk+iqMzT5dkbuZeDk/HUU2/hoyU7CyYLsW4q5zEXqen7xGuYNWu9yV/QNik7JuXOmPYR7rqjMz7/5KSJL+7DEhb2jk1xmsbSnJDC0OR9r8iEISgLnMOBKHYc2orm3Zvi0QHN0Lbfo5SkWB3Kdi0AFftIJGIUd0sW7rjjDvzP//wPfv7zn2PixInmlZzph4Z53cSAZUYFnInh7nIYz3TufO54va8YP276HvQ9KAYUA4oBxYBi4PxgoBwIg6PQv/LyEtxwbRvcWG0Q/vrX/vh7tSfw+z81RnqOszQ5ubpcnBpuw5krzgjkjhYEuj9c2kLqao8+PafCx8FvcXn5Tjtee+1D1L+zO+rVG4gpL36GqBRRqMg7afn56qxNuOnmfrj77mdNoLt9w4e+ifp3dMOzz7yHOrV64915m00aEgnnBpj+4grcfGN3XHttF6RnOMHueuw9y3WX7aQs/CyOMHD0nEorR7upwNLT8TTo0oysc1FySJT9mKxHzxOfH5DMcc97hocD+SWOpIeEMLCMA+n7MWPRVIx8cxju7fJPKSgP/kjhtCSua/ALgQjEfAjlyeLoPLmP+OA36x1k/UDYCfdHvJJGLBPSoGBU9lVOYqUgUXj++edx+eWXIz093Sjtfj8X1APvvPMORo0ahd/85jcYPny4CUv8obBWLsrV3ltywAyvvPIK/t//+38mb3Fy7NatG2rUqGEsEYnl6/P5+WFSOaocFQOKAcWAYkAxUHEwUGaEwSrC+XELwLHjmVi9OgUL3tuDJvc/izVrT+LLL7bIlJaQKG7AgQMRfPzxCaOoLV1xHAsXHYaPiqvEhUQXNgq2FGpH7E1C88FA5ymWFzPprhGy8Nprq2QRq+QrjDbJ7EyoV2atw8SpS82+TbRLcFQ8JoSDU5FOnAI6d5+Cpg88i3ubTTaFsx10JCDVqrfB1+uOmOfX39iA++8faO7dH0Gp+/Bh4Na6/bErRViRONMHudo+yO6jkFk9JbriCAOJwfbt27F48WJs2rQJmzdvxvTp0/H555+b8qhEU+G1nl863vsZJvchWaxMgpB/UNq1S7JsTfASDiE6EbPr0elz+rkjEglDUAiDNxKUt5yPTVkb8YBYGuStITsUX8sgSr8vzyOTlbLw+ZEP8cZXE7Fg03Ts922T6p1F0vtzt+G9La9jZ2g9lh1YjLc3zMbaw58jNy+jyK5FVOx56vVFF12EMWPGSD3SBekP++al2Sju6tevjwEDBpgn+2PDdHQrVqzA+PHj8fLLL2P+/PlGXiQOlCfdjBkzcN1115l7++GWIcvbtm2bacO8efNMvQxTa0PF+VGz71yv+k4UA4oBxYBiQDFwfjBQpoTBmXQTEVWSo9+OVn9MlPGmzZ3RX6OQiZLOqUPPj5uPOrX7oWPn6bjib81wzQ2t0eS+QSYJFWuqc0b5j5MDUxzvXZ7xTHfltY9hyVJqwY6STkXdept9/KRleGHqErPhK1tnlXnmmTj5Y4yb+CEGj1iIJs2nMMhYInjdssWDxk2fEnLhVB0SvfvWWh2QksJSrLO1ALfc/gR27/OYCHcd+w4CfZ6ci9ZtX8WGDSKUYlxxhIHJ+/Tpgx//+Mf45S9/ie9+97tGif3Vr36FDz74QEhJfgFZsEo1r35RboPhCGIhkVQ28EyrRXj6/uV4/oE1eLH5OvFrMenBVRjQ5E3s/swjloY8hM3WqUUBV0AYJM4rC5zFXoC1x1aj+eP3SstCyA1ny0JorxAHLw7792HMnGG4s1tNtB15L5r2rokH+t2BXVkbxPKQgy/3Lsdtj1VD98ltcVf323Bnx7po9Pgd2HJ8LYIhp15rDRg3bhwuvvhiHDlyxIzwW2LkVtjr1q17GmGgvEgiSDY4demSSy4x93/9618ZZUhXzZo1QfkxzV/+8heT5re//a2px05/4g8P62revDluuOEGY+Wx8tUfpaIYUXmoPBQDigHFgGJAMXBhYKAcCENYdPqgKPKcNpKPg8dCaNxsiFHSHDXdBMsIL/Bwy4l4rNNzJu5EJnBnw/bYs9dZzGqmDlFJt7o4rwmecSQNV4mFgesT6KjYU1F3e4Y/P1lGmqcuN7NwuGzaxosujdvrPWGWPg9+Zj4axS0MEdYlbvHivWj+0AvmPixtJk24/u+PYOFCh6A4jWJpjrv59ieFMDij3wyNF4M587bjxlv6ocYtIzBk6Eyb/LRrcYSBX0C6u+66C9dcc03BlCROx+EIO50dGbcKLRXdQCgMn0xHiopn41fM2IMPx6Xgo5GH8PEz6Vj5zHEsG7kHSyZthWe/yCVUEmFwvgT+gFfesBfrjnyOFo83lprFuhHOgDecg0O+dMz6Yipqtr0aK/d+jJORo8jMO4JRC/qiUY9bkBs8gexYKmYsmIp6rW7BscBBpAfTMGbucPQc3UnaKtOXhJCwD3Tf+c53cMstt5h7WgUoB8YlEoaBAweaNPaHig9XX3013njjDRPOjw4dOuCqq64yzyQeubm5srblKVx55ZWmvD179uDo0aMFdbAs1sN3MnjwYEMsaPGw8rVXW6deL4wfSX2P+h4VA4oBxYBioKpjoBwIg2NhiBnVGjh4FGjywIgCpc1uciRT03FPwyGiIDrKOxN07jYGb7y5xqQtLWFwLAzt8WGcMFglnVd7zwJfmLwME6YuM4SBeRhHd/fdfTCg/0pz36PPB9LWWTgpU3Ns/GefncJ9zceaePvxt+seFItGin2Uq6UFtDCcThhs7Otvr8WY8ctNvvgSBFcZzm1xhIGKK13t2rXxj3/8w0ksn1SUq1WrZp6pwCYq0wHJl+XxID8sbEEMHwtHbcL7Q3dhyZAjWDE0DcuHnsJHww9j1pC1SBUOlJPLhcXO4uJkX5aAEA9PULZVRS5WH/lMpiT9U3ofhE/WI+QEPcjI96DPS53Q+rlGmPDeSEyc9zSmvD0CXcc+hJvuvwap/iNincjAlLljMWb2MKEdWabtc1bNRJPH70Sq54SQD5nWxPll4mhRoQWBjoSBcqCnwm/bd9ttt2HQoEEmDeMYTvfYY48ZJb9Ro0bGQjB58mQcO3bMWAloQaCjBYOEwTrmt0SAV66hoHvhhRdMWVu2bDH5WYe7DbYtetV/MooBxYBiQDGgGFAMVHYMlDFhoKLtrCuwCthBmfrf+L5RziM157j2TIW50T+HI9WlnHfoNA7vLthr0paOMMg6BEl9pVgY3ITBEgW7DoEFTp76KSZP+0wW2BaSAYb/7W8P4NaaQ1DjpmGoXfd51Ll9Clo8MppRxu3Zk4fG944CLRF0JDi31m6LAwcdpdQJLfysKVOS9iSxMDDFfiFP6zc7+eJT6Aszxu+KIwwEHl2dOnWKEAaOkNPiQGcVaSrWVun1i4JPC0NE1iDQ6PPGU8vx9tDVmD94I+YN3IK3B27CW4PWYUq/JTi8PQZvIA8+WWeSDOh+Gfn3izKfGcwUlT8dnx9dgcbd7hQO6BGrQQ4yw7lID2Wh8/Ot8Njk+zBu0VCMf3cIpiwYjikfjMK/P56G9MhJ5OAEJsx9BqPnDRbakY6ITHN684vpaNavIVJDxxGIyqJoUdzpvv/976NTp07mnko+++XuH59pgbAWBpuGGbi+Y/To0WjVqhU6duxo1ir88Ic/NGXZ8seOHYsrrriioHwrZ5bLNJZY0FLBqUtffvmlWTxt5WPlbJ/1qv8kFAOKAcWAYkAxoBio7BgoB8LA5cSFLkMIwYMtnIXEDLU7ofK+8T/H8WKUfl47dHwJKz92NPOwzC1KuoaBCeMVmLMe5P7qa2RK0kfOlCRGkTDQc3qSdS+9JIuEX95mHwviNm1Nwdr1R8zC5wGDlst6hVcL1i8wMRc9/6NaTyx6X7R9cePGf4FmLZ4098k+atXt6yIMziaqTPfVmlw0bfI8Gtz1At6etzZZVhNWHGGwi3wbNmyIG2+8sSD/c889h+rVq5tnpuHIfFGQRmUkPCqKdq4sWhZF3CO2H+lTTKwNUfFiEIBo7bL3rMhMOEUwwoXShaP3tiwunPaFhRiETwrvyBSSkIP1vhW4p1dNycw1DTIlSQry+r2YsWQS6vasjo35X0rMCXkXp7Al+jkGzuyJ9MBxSXUSE99/BiPee0KWVZyEV8jG/K9n4b7e9YV6yIFwQjrsyP73vvc91KpVy/SPyjv7x5F9ysk6TtOyuyQxjPF0lNOsWbPMPT++/vpro/Tz3q6R4C5Jv/vd7xhkXIYAdtiwYaZ+toH9pxsxYoTJm5KSYkgE67Deykiv+g9CMaAYUAwoBhQDioELAQPlQBiMfoVXX5uHW29tjDvvaoc6ddvhttta4pqrayEjPWh2SXrhhddxS812uKtBJ3C9wMzXluHmWx9B3ds7y85Kn5hCqBO69EKnYEMFnNs8YR8kFVdf0wEffrTDySOf9ig3BgwcNFYWKbeQdnRDvfpdUadeGwz/1xSTlh+0UHADoZFjXpX1BS1xW72uGDJ8YkE8LQszXlkuSnkTNG3aFXXrtcLnX24tiE+8qV23D1L2OQqrJS5Ms2zFdtx+R0fpX1dMm/FOYraC52SEwY6Gt2vXziitHOmeMmUKZs6cWbD4mQuiCVAqwkWBGpadhmTNgawNoOeIeMBPL1/oQMycqxARiwLXLkRkRbdfSIUzak4rQ6EnYfDLgmZ/JAvzP3wTD7RriEd6N8GDXRugda/78WCnpli8cqGsP/AiJXU7eo3pgsZd7kb7AS3xqOyk1Ozxe9B12GNinUjD+pTVaNS2Pu6VvNPffhH7ju5Fsw5N0FzK6DG4u5EF20DHBd5///vfzT3XHJA0UJFfs2aN2U6VsqC3i8C55sG6m2++2cT97Gc/M9OaaF2w1gSWT4Wf8mL+H/3oRwWypRWHdTCN3b52yJAhJv7kyZMmjsTFkZP+MBbFm8pD5aEYUAwoBhQDioHKjoFyIwwembuzZ+8B7NojPuUQdqccwfYdB8xiZyp0aWk+bNq6H3sPpBv9Lj0ripT9afKcCq/PmTdO5dk9kuzYDRhXaMWIyNSma6/tiGXLnKlMLIzbpdrx55zcKLZuO4itu44Yv233EWR75DwCm4DpxR9PTcOOPXux9+BhHD3hbPfKsmxJa2V0etr0adh/8CCDTfluQmAC5aOOWBj2H3Danxi/9+AhbNq23SSNSgNOJ0MkSPnIysrC/v37iyj+VJQ5+s1pNvRUXE+dOiVb167GqlWrcOjQIaNMk1zQu4HqfqaSa31xaRyiwNF1t+eXX85UkPMVPN4M7Ny5Abv3bEbK3q3Yk7IFO3ZtFrmmm12Q8szmtVHsP7QH896dja/XrzJx3D3LG8lFWs4pbN25GVu2b0GOJxtZuVk4ePggtu3YipNpJ81OSdZKwK1MqehzS1kq97YvJA/r1q0zfec0oS+++AKffvqpsSKwf3Rz587F3r178eabb5q1CtxNio5lsxyms/Vwy9VXX30VJ+Lv3loyaLXh+Q+04jRu3NhYOJhPCYP+M3B/f/Re8aAYUAwoBhQDFxIGyoUwUFEuydEq4HZu5d2GUzlMJAykCVwhwfJZBJ+4FuCPv78fz4xYjB07nHnvLM9tZbBlJrvashLjLFHJS6LVx0hkJIPtJ697U4JYvvQYalTvKkqqs2DXls3+utdTJNblfi6OMFBJ5dx96zgCbke/GcZ8VpkuCbAsxyrKvCZPS8LhJgvO1BwShoAsbA7J1KQ8Oe0tlkfvNz4q85n8EucL5hrvDeSIfOwWuzFEYlKvWCh8ITmLQQ5xkxAhbXLCclQU97AcSheT/uTJGgU5x8FOiWIf6TktqUuXLqbrVtFnu4tzjGPfkjnbX8azbJbHq3WUqSULJBNMt2zZMmNd+OqrrwqmIRUvO/3BtDLWq2JBMaAYUAwoBhQDlRMD5UYYrEJNpTnRh2VFM+NtGqushUVZo4u5yIJV3BnO9FSZrSJuD4l75OHheKjFUJmm8545iM3WZ4iDZGJttBQ43toMnPJsO1g+HfNEXYo566eibq7SrogcFkdn2hInE6xvwYK16ND+WbRt84wo1CZJQTudp3gmucSSMaR4ItaTzMJAxdYSAiqrVGY5+u1eAHw2X8qSFd7iCIMsBBblPiynOofltOYgyYOQgJDc+wIkC15Zw+ARK4O0jVeZAmVOfOYJzpKPeX2yJSvDuH0qT37O8eSYuHBUtn+VOEMeos60I1pV2Od3333XjO4flpPx2Gd3P9kPKw+r4FuZ2HCbxsrQypHkgHlIEBjGdO40vCeZ4MLyVrJwmmltHUzrbofeV84fRH1v+t4UA4oBxYBiQDFwOgbKhTBYJdwq7smvVOCT/1HBp+JsvVW4WW5hWcwfNc8cvacOzpH8wnjeM41YIeSUBTOiLVcnj2OnoOpvCYg7H+tJ5orWn1CXRFqC4pTFOtiTs3PFEYbyBXNxhMECisoyF0YXerODEtc5lNoL6aE1IYnnOQyJ/f0mCrolDIlllvb5m+YvbT2azuJLr4oFxYBiQDGgGFAMfJsYKBfC4Fa+nXs7um+vCcq26NTuPFSyLVng1TreFaYj2XAIQ2GYO/7M9+eVMBRpG+t2yMrZUobKQRj4JaZSX+hLTxQsqTg7wvBNvjTWKvBNytC8+sOtGFAMKAYUA4oBxUBVwUCZEgaj6IviXPRKldlRnwuvjhpdNF1CviQWBhKHwjwskysV3GG2rjOX7yYZRctgLcW7xLQlP0dN34sv7fQYSxj27dt32ih7+YGUFoZEX/KPhNlFqdTWBUsaxMIgVopEn8zC8E36/k2sE9+kXs1bMmZUPiofxYBiQDGgGFAMVEwMlBlhOF311RCHypydHCxhSNwlSb9QFfMLpe9F34tiQDGgGFAMKAYUAxcaBpQwnJ3+Xu6pLWHgdqBc9HuhAVD7oz+qigHFgGJAMaAYUAwoBio2BpQwlDsFOLsKSRhycnKwe/duc+WOSWlpaeYsAJ4HoL5iyiAzU06olvemXmWgGFAMKAYUA4oBxUBlx4AShrPT38s9NQkDt/LkQWx79uxBSkqKufJevcpAMaAYUAwoBhQDigHFgGKgrDGghKHcKcC5VUjiQHMdzx2wB4wlnhGgz87YpyfOAAAgAElEQVTZFCoHlYNiQDGgGFAMKAYUA4qB84cBJQznpr9/K7l42rU6lYBKQCWgElAJqARUAioBlUB5SkAJQ3lK+zzUpaThPAhRi1AJqARUAioBlYBKQCWgEii1BJQwlFpUmlAloBJQCagEVAIqAZWASkAlUPUkoISh6r1z7bFKQCWgElAJqARUAioBlYBKoNQSUMJQalFpQpWASkAloBJQCagEVAIqAZVA1ZOAEoaq9861xyoBlYBKQCWgElAJqARUAiqBUktACUOpRaUJVQIqAZWASkAloBJQCagEVAJVTwJKGKreO9ceqwRUAioBlYBKQCWgElAJqARKLQElDKUW1bebkAe30fGqXmWgGFAMKAYUA4oBxYBiQDFQXhhQwvDt8oCzqp2gUKcSUAmoBFQCKgGVgEpAJaASKE8JKGEoT2mfY12WKEQiEahXGSgGFAOKAcWAYkAxoBhQDJQnBpQwnKMSX17ZSBbC4TD27t2LHTt2YNeuXdi+fbt6lYFiQDGgGFAMKAYUA4oBxUC5YEAJQ3lp/udYDwlDbm4udu/eDZ/Ph2AwqF5loBhQDCgGFAOKAcWAYkAxUG4YUMJwjop8eWWzhOHgwYPG0uD3+8sNHEpOlJwpBhQDigHFgGJAMaAYUAwoYSgvzf8c6yFhyMrKwr59+5Qo6EiCYkAxoBhQDCgGFAOKAcVAuWNACcM5KvLllc0Shv3795c7OHREQUcUFAOKAcWAYkAxoBhQDCgGlDCUl+Z/jvUoYdAvqf5QKwYUA4oBxYBiQDGgGPg2MaCE4RwV+fLKpoRBfyC+zR8IrVvxpxhQDCgGFAOKAcWAEoby0vzPsZ7SEoZAIKBTlnROo2JAMaAYUAwoBhQDigHFwHnHgBKGc1TkyytbaQhDKBQ678DQ0YRvfzRBSeC3/w70e6DvQDGgGFAMKAYUA0GUK2HIFy07v+DPqtwxubE+T+7zClI46ZnndG9zu6/5kpclRcTz6pTmvuaZMFubvdp0th4+2zheGe6UEpP7qKnF5uHVycd2897+xcMl0Al3rizJcQy1pdgUNq7wWhJhCJBBC1kIhP3whnKRHclERjQD6eL98hwK+hEIhoVMcCtWL0IBP8JiiQgF+OVnGOODEhZCRHwwEDbP/pAPvpBHyvDIM89+KHvrhV/akhvOQWYsFel5x6Q/OfE22h+qAPzSFqYz/Tbtl7hARNIFJYzx9EHxIXN10jE/CRXlwP45nn1mPl9I8oS8CJi+yjVeLmXkyInlMR3rcO5Zvi2b8nTkJydOSlt4b2QsaZ0fmELZsY0h8WEjf5+U4fjCMJtH6uZ7VatRXIaFctEfbZWFYkAxoBhQDCgGyh8D5UIYZGfQkl0+VfxCNZ+Kv+MLlW2rWttrkQLj5eeLmh+SCCr51kXlhs+hPCr7hXGHjoeRG3BqZRp6OksUeJ9yKIQT6byjY0xEWhY2T2F53LM3F1Ep1CENEhN1Sknsbl48DdMZZxLwSQrJp5d7+iSuJMLgkAVRjvO8OBk8gq+PfYlPDq7EF0dWIc1zBGFRhP3BqChdPlFUc0Wh9YknaXAIBBVWKsMkC1G/KNSBqHn2ivLsCWfDKwp8QMpwyEXZgtMnJEVUd7y0+AVMXTpG7rKEDDnkICRtJPmhYk8yQ8WbfTI/GIGYuVLR90l6ryj23lBY7h3S4PyosG9CLKR/AZFHIBgx/aXi7pE8fiEngVCW+FyjxDMP4xzFnuUFkSuepIHleqnMs02i0EdFllE/y4vFfTguY4ccOO0MSHp6h7BFDREgSZH6xPOdRA2JKJQxT/f2er0GETz6/WzIA9NGBYvEDvOyrG/jx5VnhrAtdEam31I7vo2+a52FWFZZqCwUA4oBxUDlx0AZEwZqxo6CvWnDcbw09XNMfWktZr62HVOnb8HY8UvhFX0iZjVsXpN5ahxxx+hC1ZpPVOQdzyfWNv31TZj04qeYv2CjSRsx9MPJ9cVXKRj+9BzUvq0HXp+9zqS3pCIqSjtLojt0HKjfsD969Pq3E2BiHCvCxCmzMXjwbPztumam/SyZdgXbDz5/9dUhvDhlOd7492bE4oU66Vic7WT8lkGuXpnH+EdJhIFKayAcwn7fLgyc1QO3dLkO1Vpej7ot62LhijmI5FO5DoviK4QgrtwGxNLgDVNR9YhCTiWWI+0kEE5aKsVeY2Ggss68eaIYl73CSWWf7s429dBicFMcyz0MXyQgVge2I65o+zl6zy+dX5Rsh/zwR4jxjlWkkDCwzTYt03MUPyJhIZEF5RaTsmJ+WgykbJFJJCAWGLlPtKZY64JDFigbv0MyDGGQcgwBY5soR6d9DCMJoEwLSY5P2sNwkgySNFoaHPLG+0gCYaCyTffUU09h48aNRvkv7Q8uycKnn36K2bNnm9PBz5ZwlLaektKRKLDeVatW4e233zZ9ickX4WyIT0nla1zl/+ej71DfoWJAMaAYqDwYKDvCQJ3YOI75A4sXf4mHWg5G0/uexi21B+K+FmNxe4PuOJYWK0ZVNtlMHIuyyra9d2LtJ0NpQchHWG7/eEU7PPzoOMybvx5hyejQCUdr37brJF5/azUGDJ6Hl2Z8VoQwxCQlyQNLGz1uMWrU7I0m906IV8L8rAF45bX38e6CPbitbmekZznlM5yeLip1Ll++BUOHvIGaN/fAsWNOOPvg9EPsJzYxw+S+OCtMSYTBJyPu3nwPvji+DFc+/Ft0ea0lVp78AF/u+xwHUlPgj+bIyHgWfMgW24gorMiVkXuZtpR3FB6ZvuSLZMOXn4GgjOZ7kYHs/DRJkS4j/TliqRHFOE9IhYzKh4Q4lPWX2hfxifRjeOXTlzBz1UTTZvaPU4ZyY5nSnhx5Nz7k5Keaa57csy++ULYo5blyZVpaGcQKIIo7pxNZRdwhSdnSf7G0wCN9TJO+njRlBkU2IQnxBbOEPIiVQZ4DIg9aOCiHbJkixelRuWKh8cizTz4zJD/vWV5AnnJCmUIiJEbakBuWe2mj2CQkNhtpsZOShnmlrXGrjTePffGIZxlZIucMyStWDmM5cX48iJj58+fjoosugsfjEdLpWFL4HmgxSObsO2Lc4MGDce2115r3lkxJt4TEXY7Nn5dHlAou41ebxloqWF6y/EznXk9DwrBp0ybTh61bt5pikrXFWkNs/XqtPP9A9F3pu1IMKAYUA1UDA2VLGAqUYpIChzgcOBpGk2bDRFlyrAE+0U2o/nywdC969JmPk5lAp55z8XD7l7F2q4zYSpwMcpv0VGOsl1vHsY54PTIBw6S74vqueHfRZhNPwuBMeIrJNR+huGY+ftIiTH5psSnfsTBQXY2IB74Wa0iXHpPRseuruL/Zy6ac/HxO8ZA08alDmdlAg3s646QQHjqujqCFwd0+EoE6dXpj7z5fPI1DLlgfXcq+EHbudO6L+yyJMHjzcrHx5BpM+ngkbujwezwxty3mbJlhpiZ5ArnI9WcKETiB93a/ifYzWqLFlMYYNK8rUsKrjMLswymsP/4+Hn+1JXrNbYMNuWIR2TIBLSfehTYTH8DXaV+adQW5Xq4nKLsvBJXMo5mH8NzCp9FvTmcMXdgVu058jWiYI/9h7PZswr8W9MHjr7XCp9nvo+uUR/DouCZYkvKOTMdKl+lTJA6y5sJM+2E7uS7BI0THh3yfTEGSck5FjuL5D57BgLe6YcaGsfgksAjdZ7dGs4n18e9V00R9TxdZncS89dPR4ZWmaDG1Hrq80gx7wl+J4p8uyPBjxqoJ6P9WD7x7YDZ6vt0eDz7fEHO2ziAtQFY0GzmxHBzHQXyWsRi9Z3fEsEX9sQtb0X76I3jpqxdwUtpwNHIYq099ge4zHkb7qY3Q6/WHsCb7U6TKH6dlUc6UB91VV12FatWqmXu3/E+dOoX+/fvjhhtuwG233YaHH34Yw4cPN9YEKuR0fCZhoGJPhdy9JsISjmHDhqFGjRqoWbMmZs6caepm3Nq1a00YrQPLly9H8+bNMXToUKSlpZlpUiQvdEuWLEG9evVMOx588EHceOONyMiQ9TNSJ6dTEbu5ubm47LLL0LZtW0N0EgkD69u1axc++eQTk8f2n2W4+6z3Zff9U9mqbBUDigHFgGLgTBgoIAz8584RRXref2NXUARvOPpPtR04LIThgWZDzX1BEnmaN+8zUX764O83tkH3PhPRodtkXPKn+jJKXrjOwCrjvBZx8YK4IJnK+BXXdcTSj1NMkojEiaov3qEDdmx2/MSlQhiWuwiD1OPoQWjVZgxWfnkEI0YvRJP7JplyKBOHMDiVGcLQkITBmaYUk/hEwsCUtes8IYTBUeJs+1ng8o+348YabXH11d0w5cUl8TrMpcgH683KykKyk56Z8MGujVG38z9Qf0A13NbrWtTrUB19RnWXmHwzSt77pTao0f5qNB58J7qMa4fbuldHrZ5/w/Lt70oKL/793nQ0frIuava4Cs2fqofbu96AewfcgZoP3Ygl6z9CjijbgXDZfZGoyHIk+uPVK/DIsBao06M6Gg2vgy93LUco5qxXWHf4c9zxeHXUfvJa3Nb1OrQdfi8aPnkzbm11LY5l74Y3Ikoq22lG6J21Al4Z7ed0o6gAKCjTtrJldH/87Odwf/+GuKdfLbQYcD96ju2KfhO7Y9IbE4ToRZHlP4peT7fF4Jnd8My7fdFxfDM07HaLYIQWGi8mvDMa9/Sqi9u710CfiZ3x5JQuuF1k/8W+jyWW1hsfpi2egFukXf3G90CvcV1Rs4O8m161MfGjMUI7jmPxzrdxS4dr8eS0Lpi+9Hk8Mbkz6nT6B14X0hKIOUoy3/msWbPMyPzx48eLKM6U1x133GHiXn75ZfTq1Qs/+clP8Pe//x3p6elGWf/+97+P//7v/zZpfvWrX+GXv/wlfvazn2H16tVGgT98+DD+8pe/4Be/+AX69euHvn37mrRNmjRBTk4OVq5caZ5p3fjpT39qiAfL4fPmzZvN78OMGTPMc8uWLc3Up+rVq5vnY2JO4/u0PzwkKy+99JKJ27BhQ0G4jff5fCaOZQ8YMKCAVJBYJJILm0evZfd9VNmqbBUDigHFgGIgGQYuonJCksB/8vYfNO8TpyMU0WLP6oFqsrO7ELMdORpB8weG8fY01/Lh0Xj73fUF4c0eGoilK/aZZ+ryLIlKuKOyM5h3EhMP4KJnEoYrr2+PD5c5Q/c2H+0HtHM4tAUYP+FjTJ660jwzD9PRLVi4Cy1bvmjuhz6zEPc1e8ncc1A1j2sc4nVl0cIghOGUEAY6N1lwQpxm1arT31gSmOb/s/cdAFYUWdfm1VVXd9d/w/dtMKzfqqurq2vOqIAoi6JiQAXFhCKSJLsgYAIDAmJCMYCSRFBJgkQjOWcYch4mvPzezJz/nOqp4THOgzHylNtQr1N1ddXt0z331L23Ssf9uVlzNqFmrTY4/8J2GPbBfJ2ucNkVYaBahgnTRqHbkHY4885j0ebte9GfLj1TF02hkhvH+KUjcQWV7DqdqmPC6lFUaPPRY/RTOPWB49DixXuwIm8+5ZXCG5NfwNn3/h+ubXMp+k7ogS9WTcSbw9/E4jXL6W6jwOgdI/1UBKLvcizOAOUIYwmiJTEsjS1B7Q5XoWYHEoYl42k9CNMdSA5TG/DKJ11xbrO/48Fet2Fz0RJ0ea8Fzqp7AqYun4hwcR5iKdVRSUq3YhmCeifpUhVj3EKE8RBaOvd9BDe0uwozV81Ik3cJCmN5lEQ+lm2bhY++GoD+k17CCyOewLUtLsPqyBLnXqQLbm5dG92GP1p27e2dr0GL7o15bcK5KtW8/wp8OPedsvPPjXwSd3S5Batoa4izJTWaXoDWtD5sQA5WpVZwvRb397wNDZ+ti43bA3Kgizt16uQUaW3791JyFmE46qijUKtWLSxdutQp+PPnz8e7777r8um8lieeeAInnnii2/Y/sgzovX755Zdd2XPmzHEWAR3r16+fO7Z8+XKXvV27dth3333pThf40wmHf/vb3/DXv/7VnW/cuLHL/8UXXyAnJwcbNmxAz549nZVD1gHVQ9eozrJYiBAMHTrU7ZfHy3777efOv/DCC+46XatUPp/t2x8xw4BhwDBgGDAM7BkM7CMlQn/g1Tup3ky5O8hn2vsVe2XjG69LFetARZaaHqjKa9emUOf6jq44jTCkRQq7XIeuvPoRKk2Bi5KO3/3AkxgwcJ42yxRtt6MfXeuu50/ZdjAS0kmnNcDosQFhUFbdWVlEJzwxeP758Xjp5QkMDA7O++OXXd4azZpNxNAPUri1/iBUu/IlvN73MxXjSEEZYWA9a9a8H1u2Bu1K8oTckoLxnVx2KkzAhZe0J2EI7Bq+Hq4s/mwi6chhcLXblxAqWHZFGNSjHk/GMGP9Jzj52t9jIN1ptpasYptCbGkKXfq2RfWWf8ejDIiW/3+ELjMbsBwXNDkZVdhj/9XaiRzZKYzxa4fjpLr/i34T+rAXfDPdldhbXsyoB1oWwi4Y+ocgDFQIFYQcl28+MZiUoluM27tch6s7XMA4jPEkAhxqlcHJBfT/7zf5RfybRKfPJ88wH3vyJzyNM+ufQrckWkEYJRBhGQpsVuBykILhTos4+pOGk1Wcg+I4uvT5L5r3auyeU5gB1RQMIgW5xEcBBn3ZB7e3vw4PdLkbzw18Eu1fbY5aD1fB3E0z6LIUIiUAbmxZB0Nm9eMdWT4JW6vXHkCjbvewvBQmrPgEtZtdzVwxbE5uwEbGL5AW4MZ212Fp0Ry2YiVqt7gcVZuejxotq6Fmm5q4uvXVuKzx+ajXoQ7Wb1nrlH498yZNmjgl2scNpH8g5SYkBVzpkEMOwe9+9zt07drVkQfl1/WdO3fGqaee6hRv9eKrE0DvtFKDBg3KrpWyfuihh5aVJ8Kgb8LNN9/sytB1KlPLs88+6/JpWySmatWqZdepHqeccor7luh+Sr7u06ZNc/kyEYacnBy65i103x2101+X3mbb3jN/IEzuJnfDgGHAMGAYEAb20R92EQX1UmqtHsXNmzc7ReP7sTJ4VZxKOxXo5fQUuvF6KX3BIoVdC0e9RM1rnsTWgoBA6Ngd9zyNIUNWarNM0Xc7+tF15RMPSCn/x2l3YszYBcrlsgQq/Q7SoaDkF174Aj16THJuSEnue/JS9cq7cEmVB3FRlba4uEoXXH5FD7Rr/4YrS2ShqLSwEOt5ZfXmyKfST50KKTZTp0QYgtDo4N7nX9oWS8oRBnbouqXnS+PRrNW7wU6G34oIg3pfpbAVMFB2c2oDxq4ejBPrHoVXpz+NHMxDbsl61qMIAz5+A9e3OxeNnr8Z67CYHvqr8WXhWJx65//i1o7XYuamL7AuuRKj1r2Lv9X9Nd6c2RtLSuZjBY/lUYEOJTX05/c3rKoCkYN5CjSCEYmCH8Y1ls8YgI1UyTfhxier4/L/noEROQNY2+W0Jmxnv/x6vDnlWZx63x/x6sQnqI5vxIsTu+Ccu07AiEVDqMwzSDspYhCQhATBFGfZCaYkhzzViFCFKQVzb0Wnvs3R/OUGLIN2i/BqxJIiEwoM34QGT16LZz74L2W1DGuwBEuLZ6B2+4uxoGAqczNOgVK5psVVGDz3Dd6RcRM88uDr9XHPc/UcqdnIK69rfjV6jX2SNVzBWi9HbxKbuv+thYWhqcy/Gdc0vQIvTHmabVtBm8MCLMR8/puO5SXz6H4XxDDovfNuQiLv6RYGvbSvv/66sy7k5eW5d3bw4MFOIZfLkbCh5bHHHsMRRxzh9tN761VWly5dyuINPCGQki7XNy3Kc/fdd7vYBNVFebTUqFEDv/jFL9y2lP9Ro0a5jgZ1Nqij4a+0PihWQYvK8/X+8ssvXf0+/PDDr1kNlE8Wj3PPPde53WlfbdS1/nr7Y2V/rAwDhgHDgGHAMLBnMbCPCIKGbVTPogiDT3ow340wSCsWWQgIw/p1Ubom0Id7+BrUurobZs8qwaefr6eyFijry1YkOepQO0ycwvH3qZjnFgK1r38U3Z/7FPnBcPTSQ3Ys5cmC9rnobieddgctDDsIg5R8bxlYsGgLps8ooL/0YI4kMxRTp4WxYBFvxqV8J3+jh96kFeE5+sa704GFgWVNn7YV48flotrlbTBqxHrMnMFRdFiEqqBWB7QlsHacW6UVFjO4WYt6oUuriXcGzsapZ9yHM85qiQ4d3nbnK/qpiDD4l4ahrOj0VnvU6lgFZzf9PyraZ+Hmx2vi7fGv8D6SRAoNH7sJF9x1Em7pehW6T3wSZ9x9PKo9fDrem/I2XZTy8MK4Z1CtJeMDWpyE6o+ei2u7XInHhjzqlPCCJJ8FlfmyOQ+ICX/vb7rWXAoaOlRzPiQZV0A9nZaAImwPbcemghw8/WZ71OlyOaq0/hcuaX0qru58Lmq1uwxzts/D/IIvUb/LVTivyTG4rs0FmMlRoep2vgzVm5yORk/UpSK+BfGE5poQISFRYNmxKN1h3JCwnFsiVYiVWxfgi5Uf48HnbkKDbldi8prh+GT+R9gc2YACTnQnMvFQz7poyPOTN4zEqGWDUa9LLVR76DQMndEXq1OLsCg8GzWbXobnx3TG+hIq/LGZuL5rVdzetQ6WFS2itGN4/K1HaDE4C3f0ug43dauGWv89Hw2fuhGro/Np4Yig8xuPMJ6kGsbkfIiJ68Zi5JLh6DCwNRo8diu25AVEXc+8Q4cOTsmWRSBd+ZbyL8vCv//9b4wbN86NQiQCoGPqydd5vbf9+/d3xz744AOXT0HLskTouSmWQPlbtmyJkSNHuiFY+/Tp447peyALw3333ef2GzZsiGHDhsG7ICnYWovWKkP3UVyD7v2b3/zGBUfrvOrh6z1lyhSXVwSjPG7UPpWjpHv480YWvv275mVoa5OhYcAwYBgwDHxfGNhHysOyZexRXbPGkQZZGtRjqF5FKS7f1zLio4m45ZbGuOuuTuw9fQm312+Hq2vdgbzCIC7gjbc+5JwHz3Nkoi7uloOHfor7Gz1BxeVJjPtk6teroaqVTzwkS8FJp9Il6eNl7hqNVCSLghR5LT169cXNdR9yZTdqzN7f29ri1T5Dg5P8LeYFySQDNV99D/c07IImzbsz3qGvOy/SofJuurkh29GeSlMP3H57KzRr3hmLl6x2eQLC4Dbdz3mXtSFhoAbLRREU3vqwdFUuWrTvwQDvXpgxa407X9HPrgiD8nfu3h4derdFx9fao+1LLdDmuRboP+xNF28Rp+acs2kxuvXthIad78AtzeugXY/WGDDmbeSFN/LqKHq+8QT+26sl2r/4MNr0bIKHn26CFwe8yB55jjrEQOKKCIOwIYUuvee6IkAqjyxYOreDMJTOocCef02mFk0lkbNxGbq+9ChaPdMIHXo1wSPdGYzc8wG0eOpBLMpZjEVr56BttyZo2/MhPPZiO0yZ+THad2+OTi+2R+denbCtYCtSjFiPcUI2WS6SkWKSvNKJ2+j2lChJMNZjPB7q1AiP9HwY7bozILnz/bi/9T1YvnYJg7ppJiLtmMHhaFt3bYxbHqzNvPfivYlvo/MLLfFo9zZYumk+Xh3QC4/2aof2PVph1rKv8N7Y/mjXuynr2wYjPxvB4Wq3kKbF8NGU9/DywJfx4pAX8MX68ajf9kasiSznMLYcvDa+DT36d8d9He7CbS1vwn2PNsBTrz+Oz+d/RvLMeRnYw65n7hX+JUuWuH2vQEvmtWvXdu5Gf2WP/mmnnYbjjz/eWR00IpGTNfNolKIOJB2KO5Air9GURCx0Xs9PyrtGSFLg85/+9CdnTRAJ0HVyUZRLkoKQ69Wr5+6lEZlEOrSofq+88oobwUnlK4BadVBcha5XHfXcfZ19zMT06dPL6uexo7pUr17dXS+rhT9eEZ7smP3hMwwYBgwDhgHDwJ7BwD4KnNSoKSINsjTIwiCF4btZF5xeUfpDDZsLOxKpTMD1xKs3Pj/E0X8KU06Rl5IdipRg2/YUCphHVySYnzqfu4b6+9cXZSqfeIg6I07+1z2YNGlL2TVyF5KVwZVLrT+3gKPvF+r+4DogFGWZtcHg5jCVztz8IhRwRNRITLEJgZVCpGF7fgz5rHsByU5uXhHCVFJ1PAirDu7lyzv74tZYzhmjtchNSNYHDc2qJuXFWZeAS7jzFf3sijDESAi25a3DxoJNnOiMibM7b+C+JjHTyECRCP3IGYNQyBmbV23NoWK+HBvzOC9AcQIpzm+QjHKehcR2uoFtwcb8TdiUvxZ5HIq1gNfF4sFIN3FOahYEEu8AaGUJg5RfKZB6uYPefz83gkiDXIjY5877hGKcpSC0mfErq7FpWw625q4k0VmItVtXIUF/sYIIHYDCbN+2VVjPY4XRXMZ+LMXSNUuwess6uhzRssAHrxmc5YqkmZc14ZqS3J5inEeiIFKIDZTRMl63Pm8Nh3Fdx/LXkThJyaaPP2WmWbxXbViBr+Z/xbzrGYgdwtoNy7F640rkR/OwcfMarOd1KzevZh3yKPsNWLFuAbHM7dxc5DFwOp/WihSdqzhFGR9nEd6e8iru/m89bON8DmHGV+TTly3GAO8Vm5Zg9vKpWLF5EWfl3kQqSXsRn5kUZslXy1/+8hdcdtllbtsr35KlyL2S3tXJkyeXEfx0ZVtWAl2jd1rvuFybtKSXLxekxYsXO1egXNZfi9ychLnbbrvNjdSkYyrHn9f1+j7o3mvXrnX10BwLKkeERc9b+fXsZT2Qe+Mf//hHaNhVtUvH0+spYqFr9A1Kb6P9QdjxvpksTBaGAcOAYcAwsKcxsI/+UEuhkKVB7gj6Ay5lQ0rDd1+kZitgMtD4VaIbfpTKFJ1S+I/+/7u4TdKPc8p8X1t03dcSh0/lsWP+71b2kHZF/35fuMtkYQgUeoUCU2llUo2UgkFRy1ci2Nevu44bIgPlh05V65RH91RAdYo92VpkhRg7ahGaNXkT51zUFktXBspakJ+Ty6XoNqLrmMiTdrnskjBQmY+zdzwixZwMqzBR6MbyD8zKibYAACAASURBVFPhz6eCHGWPdYrPMxzmNGIh+oWHOGlZOB/bonQz4rFiBhxHw8xD4sIqcd4DjljEqbcTdOeRy1Aywt56uhEp9iAdqFL4pNx5BU/7UgTTk1cspSTudK16/OU2JEVehMFNCsfrqQgnRWJKU4ouRgmWG6aARAgirHMRg7A1K3PczbHA9nFbMy/HdIxKf4QMUzM5q87ajsR0D7WDNI1+bim2N0E5xchAw0xRAiOcYLC0CB/Py1VKxDLEc/nu+gSPs44sM8ykmaNFSshHnBUqQcW5iCmZT6sA5ZWivPISm9Hzg8dQtfXJuKLdKbi67YV4dtCTfAtIWkhOwpyhOsoRmyKRPBRxsjrNNRFh/TXpXIztlNyUtMgKIFcdyVnKt5ejJ2xS3H1Pvt5Zf96vdV7PRPnLn9c9/HGfR/eR8i5LgIZRvfDCC9GoUSM3gpLq48mfyld9dG+V4ZOOqVxfnu65cuVK1waRCh33mFEZvl0qR8nX29Y7v28mD5OHYcAwYBgwDOxpDDgLww9DFqRiSBv2anWgSOuI/OvlmqMzWuJU2hQILAXDL+IrRdLeuJRIA/8Gy6AhE9GHbkZjP/6CyozKYWIZGhbV9/L7mgUTsWUuX7dWPVx9WSntpydV0V9dVBwQIx2bMW0x3uj7Ad7qP7as5j5f2QFu6FicSqxcoSpaPGFQjImUsZ0BI7cgKZpUjjk8aZxaf0QjAkmZd0o2FUan2FOBjlAhp8JWSNIQ5YhEcrsqYopJGSUxC5MoRKWAhkgYyYDU+x93VoCvv6ReIVR95U5SrVq1ryXNFSA3mOuuu841a0fdNTpSaaJSLtehGFMyQcWT9Ys7pVkWiQgVSiYq6AWF7LmWss26y9rh2sy1m6CNjEBrBTxLNsEMz6qzymYALduRIHEooqVC94hRTlEN5cp7RQgOJzfeI+GIDMdRopzilEecZqmCQsZF8HhURIFJBCY/X0RMLlm8B+uXYIqFRbJkMSGxSBRg/NTR6Pb6o3hh4NP4eNoI1/58WkmkwEdZRxG6cJjlRNQbr6TjpfXnPbysdOFTTz2FcWPHuzLUdgWha5K6WIrlSFZFVNxlSRI22FYnAxIQlalyJM+oZEWyFSUZ032kqHvFXXXySRYCbWuoVD1XWQXkZtShQwd3f5Un0qDnLwukr6drF8usaP/jjz928zSoAFkvdsYv20CiIKKhMsqfs/2vv3smE5OJYcAwYBgwDOwJDLgYhu/fsuD0C/vZjQQqY8XZNWHY+aXxSmBlgJSuNJa/rvx++fKkGHrS8Mknn7iJvrT225r4S4qiZgLWbMHKW76M8vvp9Sl/bnf7cnfyVpBgJKad5aLrVWen0HIdlbsWk1vznDvv1iIHzEcCITemOImB1iIfvg5eKQ72peRL0d057aDCAQC8Qp0uVynK6fu+/PS1rtMi8hzl6AByndKIT5rFWu5NYdYrzHpHRRhUf408xWOytohEqfw4SULEWV9kgdlBTNLv47d92yrCZXkLwO7q7ssMJEBLGtviy/fn/LqyZfn8tv46vk0mJhPDgGHAMGAY+CEx4EZJkjKg3v2KFAX/B9/We0YC34Qw/JBAKV+2lD8peuppVh2FH7+tfY8lHc+kKJYv88fYVw9/RNYXn7QvpZsp7shBOlEQWdD+DsKwcx0rJgwBgQgsBsovOXmlWGV52aWXm7694x66bzphodLNsjTSlNyfihhnU6wRp3hM1o4ICUOUI08FlgaSH907wXvTCiWyoKBqb8nYcQ/7wJosDAOGAcOAYcAwYBjYNQbcPAxGFvYMGajMXbOVMOjF8spveg+6V451TO4r8m/3ynI2vIyOMLDuPig6fa1Ab1kVnIWBLkaBsi7CoO2KXqRvTxjKl1cZK0z5a5zlQy5UsoA4Fym5YYn8kCT4NQPjY4qZkJXBCEOG51jRs7VjX8ebycRkYhgwDBgG9lYMuJmefW9wZRRYy/PjSiCbCYNeGpEBb1nwPeeeNOi8FGGRh2x5wTISBircKUXHpy0KuncuSpUkDFHnCuTdk3b9UZWsvJuPZFQxYfCExFsreA1djBTcns85MgqK8jgeE0fBchYGEh0XExG4LGmkrMIIYxIY85AoIpEgWfjhZu3edVuz5dlbPew5GQYMA4YBw4Bh4NthYB8jC2kaYhZuZjthEBm466670K5dOzc8ZzpZ8C/lD21h0OhFSv5+u1pnIgwaAWv+/IVo2qQ5HnqoKZ544ikONbyCQc4alSmThUH3lDIfKPQhBmVL8dciEpWp3bK6pC8iDrouk1tSnOUrqV35DKreim2cAi4f07Z8ilcn9OAs0wUM1GbQOEe+UjyHRo4KkbykL4kiBXubS9KusGHnKvcOmZxMToYBw4BhYO/DwD7pSoVtZ58Esp0wSNk999xz3dCZCnb2HxGv/Pq1P16Zdfo1mZRulRMo/xqhSD79HNaWOrISRyvdkRg3HOewqhr1yd9bIzOVTykObbV27XqO6nQDzjjjTBx00MH49NPPaR2RFSXzh0H18/UVEdA9GjRo4EYG0rPz90xfr1q1yuU54YQT3MRrQp0IgxvNyLVLsQsaxlVDxAbDuep6tTdEwrB4/QI38dut/70eVZudzfm6t9KSoNiGIN4hwhGRNObWDTfdgBNO+jvuaFCf843k0dLA84zdSK+LbZs8DAOGAcOAYcAwYBjYHQaMMGQfR9ipRtlOGBSnMGfOHPz2t791oyQJcFJ+NVGYFGkNpaltHZNCLYIhq4RPUrh1zMc7KF9+fr7Lr+Nqv9YVATnCXnf1pidIBuiZw4kCmAqYNHEzU4nWnAKjyJEGKuVUvjX0qY9NSF/7EZHkgjRlyuf41eFH4ovPv3LDqHpC4Nvm26K1LAl+OFI/PKhmT9ZwqFrUvvKkR5OpaX6Fp59+GmPHjnXtS6WkzGtuCcUbcD4DKv8pjoxEPyJHGvzM1RrGNc65NHK2rMRnORNw3SOXsonbSudxkDtUYIlIcYjfaTOn4Y23+uLI3xyJ9RvXIVlMtyUOqVuRLO2Y/bEwDBgGDAOGAcOAYSATBswlyal12fuT7YRByrwm5RJhmDRpEnJycpwyLIW4Z8+ejhhI4dYkZJrxd//993fnb7jhBjd7sM7dcsstZdcsXLgQixYtcuWpDJWrpSIAizAUMKg3ng9MGrAUrzX/HG81m4v+TRej34ML8U6zhejTZBpWf6HZ2/ifowppJuh0ouC3PWHQviwLhx9+BGbNmhMEQMsiQcVf5OD11193dVW9VL999tkXAwYMcnWcPXsOPvjgIxx22OHOTUvDyn7wwQduNuZ0a8O0adPctRqGVotkoPI1ApLmn9AoSyI2gYVB+xxOVaMcufkiWA8Si2JOPjhz3WcZCYNGRdLcIctXLsOBBx+IdRvWmoWBZLYiHNkxk4thwDBgGDAMGAZ2jQELenYqW/b+ZDthkKVAhEG96l999RXat2+PAw44wMU0zJs3z1kK3n//facgN27cmEr4LAwePBhHH320mxxM148YMQLHHHOMK2PTpk2ux/6+++5z1/Tp08c9nPK99HqxnYWBhKGYloTRvZZjYKM1GHZ/PkY0jGBMwyg+vC8P7zXegoXDmIFz6mn2as3q7ElC+joeLyUS7NkXYTjssF+xPdMQKpTCHsyKvHHjRlcn1VdWk/eGvMf9fdG16zOujq+91hc33HAjSdGBOPnkkx0RqlOnjpOFMqgNau/s2bNdOWPGjHEKrLNgKA5DU0iT27hFcxgqKQ5b/kVMRTG2gYQnxYnZEsUhzFz9aUbCoBml48kYlixfgoMOOcgIg5EFI0uGAcOAYcAwYBj41hiwYVWpi2Xzku2EQYq7iMFf/vIXHHvssU4R9vLUcL25ubm47bbbHEF49dVXOQN3H+ff/5///Mfl3bp1q8vevXt3t+9dfK666io0atTI9erL1aciwqBA4ESUPkd0RVo7EviyEzCHaQHTvEeBmVx/+SQnDZvJW8jI4AhDxRaGgDwEQ6p+9tkXJAxHYPr0mXSpKiDpSbp6qC2yKjRv3hzPPPMM3nzzLU5QN46uVn40Jeajkv/b3/4/dO/+vGuX6u4DoEUW1A4RLJXjCYNkKBck0AOpeAUwoXMhFjwOLHqM7XkCmKb0Iq0Qq4M2hBSHUBzDjNWZLQwiDAm6OS1dsRS/+OUvsNYsDN/6I2m9TrvudTL5mHwMA4YBw8DPHwM2cZvXbrN0/VMgDPPnz8ef/vQnnHjiiU4RfuGFF8qUZX1ETj31VHd8v/32YzDxQW47cOfZp8wtSfEAxx9/POrWreusEDo/ZcqUXSp5bhIy9qLnri7E8y1fQ4sa3dCyxgtML6P1lS+j1VUvoXnNXhjc62NXnwSDn2MZXJJiVNgTtDIkEil8+eVU55I0e/Y8Wjs0l4RIBrv3uXhrSVD/fbHffgegZcvW7pybw4HzOPzmN0eRUDzrjvmPqIiCYjNkTShvYQjyxFFEK8iqmVHce+kzaF/jNTxy5RtoU+Nttuc1tLrhBWxcwhiHQk3OxgDpohCmrZqU0cIgl6R4Ko6ltDAYYfj5f8g9zmxtz9owYBgwDBgGfggM7DNjxgysW7fOBV7aBG5Ox8uqn2wnDFKAFbdw2GGHubUsBSIG7777rpOjFOV7770Xl1122dfkunTpUtfjrjxafHyARhlq2LAh50VIOfck4VJ5yr8Amq05j4pxgoG8xVLo2dMvN54SKt7Q6KZK9PKRO0+M7j4xuSNlIAwKdmaIglumTZuBQw45lLEHn5Ydk5VA74ksH+nLRRddguOOO94dkqVBhON3v/sDHnnkv+6Y6rxgwQI35KwOaL8iwuBGQKLFRBaKdStD2LY2gs2rwkxxbMoJo2AzYxrYhiKSmiTdl4oY5T1r/WQShio0nuQjVsIPJN2z/EhLOwjDUhx86CG0MKyzGAbKvjyGbN9kYhgwDBgGDAOGgd1jYB8pbUYanG6XlT/ZThjkZlOtWjVnNdCwqlr+/Oc/u/2qVas6BU2xDeqRP+2005w/vwjEcccd545t377dxTlolCQtcm069NBDsXjxYogoKKha98j0MhfyvKwTKY7AVMyUovtQgr38CfbCJ5mkYAczIQdDlbrZkStQHHXv1157DXfffQ9q1Kjh6qZ23XrrrYxR6KrTGDdunDt+9tlnu1iNxx9/HAcecCDuu6+hOx+JaESkGJo1a+byNW3aFLVq1XIxHW3btnUjPon4pBMGT4Rc4DPrFeHISEUiOSQvHOjIpRLuK36B869RDgnkbFyOFwZ2w2NvtUa1xufhpRHP4a1Rr2Ft7iqOllTIPKoHLQzJBBYvXYJDKM+1GzbQRYmEaZdzSuz+g5HpOdhxk51hwDBgGDAMGAZ+vhjYZ/Xq1TDS4PS9rPzJdsIghf65557DSy+9hPXr1zvFXkHBL7/8Mp588kmnzOsDopGB5KpUs2ZNp1C/8cYbzvVIZEDKsoYm1XLkkUe6eR20LWXa+/3/0B8h3W/y5MmMPeiOXr16oW/fvujRo4ers0Z40qL2iQT07t3bxWXIEjJw4EAoUFukRXVUWxSXIWuJrCTdunXDhx9+6KwTGlZWbVLgtwiU5OTnbhBh8uShorZqHgkaEGghSWLDtvUYPn4wRn71PsbM+RDvTRmAsdNHYUvhRs7HIMIggsURl0ieli5fgcOPOBJr128kYeDYSkYY3HOqSMZ27Of7h86erT1bw4BhwDDw3TDgLAwiDcuWLYPGh5dSJCVNLhi27HkJ/BQIgywBUnylLEvx1UupfR1PPyaFWMQg/aUV4fBkQW5MUqS16Drl1/ldKdLpZX0f27qvv3d5y4ZcpFQff97n9W3Xvq+D6ixZKPnzOqc8suipnR9//LHb99dkWgeTzFG+0WI3NGwiTLmG6WIVYSwDLRJyZ0rQmqAhWf2wrO6+tCgsXb4SB3ASunUbSGqMMJQ9n0yytuPf7Q+Kyc/kZxgwDBgGfp4YcDEMIgtr1qzB8uXLoQBW9ZBKyZGyasuelUC2Ewb1rEuJ1gfCK9JewU9fe8XfK9k6588PHz7cuTEdeOCBOPjgg50FQlLX+R/LwpDpA+frKQVc22qvtn1btda1ap8nE/6c9pVfQ7CqHXqndEyjJJ100knOLeuSSy5xANO5THVI0M1JMz5rJmelRGmSq5UCv0McEakgEqI7EgkW4zrCrJOW2+rVx3HH/x0XX3oZNm3ZaoSBzymTjO24ycYwYBgwDBgGDAOZMeBGSZJlQWRB1gWfJDSzMji9a4/+ZDthqMzL5YmBz+sVau3rnIZllRuQhlyVq5J3AfLKevnrfTk/5vrb1MGTHU8qfBnalxvT1KlTXUC03rNdtSWlIOeISIOGXw1mqw5mrA7molDwd4hkodCtaeWh21GCBsJFS5djBieTW0K3JFkXonRRMpekzB/DXT0DO2dyMwwYBgwDhoG9GQNuHgaRBFkWtNZIMJs3b3Y9qEYY9ihXcDf/ORIGvXCeDKgHXkmLn7NAa/XK+zxe0d5TL6qvh693ZetRvt7aF4lQUpvTXbl0zhOL8uWLKCi54VRjnJMiFoz2FOW2Zn/ekRLcppsSU4SB31EOByuSkCwqDo7zmBEG+4NXHl+2b5gwDBgGDAOGgd1hwM30LAVGbkgiDOr5lLImpc1ckpweu0d/fo6EwSvg6Qqy3/YxDr533ufdHZCz9bxvV/n66bjapuMiD1r7/a/ldZYFEQa5IIkQyH2plBiIHJSm4LxcpHQujgivUyo7TstD3IKenazLy9j27Y+lYcAwYBgwDBgGMmNgHymksiTIh9orLNo268Ie5QllN/85EIZv8gJmUrC/SRk/hbx610SKvktdFewcKU3aDsoKCEN6uf69Tj9m215etjYsGAYMA4YBw4BhYHcYCIakoXrqiYOIgrZtyQ4J7G2EYXeA/bmclxL/XRV5Txh2kAX74P1c8GHtMCwbBgwDhgHDQDZhoIwwZId6bLUoLwEjDD/fD8b3YU0xsvDzxUc2/aGwuhjODAOGAcPA3o0BIwzlNfQs2zfCsHe/oPaBtudvGDAMGAYMA4YBw8CexoARhiwjCOWrY4TBPhJ7+iNh9zcMGgYMA4YBw4BhYO/GgBGG8hp6lu0bYdi7X1D7QNvzNwwYBgwDhgHDgGFgT2PACEOWEYTy1THCYB+JPf2RsPsbBg0DhgHDgGHAMLB3Y8AIQ3kNPcv2jTDs3S+ofaDt+RsGDAOGAcOAYcAwsKcxYIQhywhC+eoYYbCPxJ7+SNj9DYOGAcOAYcAwYBjYuzFghKG8hp5l+0YY9u4X1D7Q9vwNA4YBw4BhwDBgGNjTGDDCkGUEoXx1jDDYR2JPfyTs/oZBw4BhwDBgGDAM7N0YMMJQXkPPsn0jDHv3C2ofaHv+hgHDgGHAMGAYMAzsaQwYYcgyglC+OkYY7COxpz8Sdn/DoGHAMGAYMAwYBvZuDBhhKK+hZ9m+EYa9+wW1D7Q9f8OAYcAwYBgwDBgG9jQGjDBkGUEoXx0jDPaR2NMfCbu/YdAwYBgwDBgGDAN7NwaMMJTX0LNs3wjD3v2C2gfanr9hwDBgGDAMGAYMA3saA0YYsowglK+OEYbKfyTi8TiSySQSiQS+7YulMqLRKLRW+rbl2HWVf24mK5OVYcAwYBgwDBgGshsDRhjKa+hZtm+EofIvkFfyi4qKkEqlvrWyr3J0vYiHkYbKy98+9j+urERsTeY/rsxN3iZvw4BhYG/FgBGGLCMI5auT/YQh6IWPxEPYntiGCAoQRT6STGHkIT8ZRigWQzSWYIoy6WPD3nuugxRcr3OR0hRVL7/LJ4UoxHyVU4yk3EvJV8rLy/vGyn6c9VI78uJbsC6cg7zkNsSiqifrWLZWfUUk1A7Vi23iuSjzBO3TOsnjQbvKf1jUlkQsgmSUdWVSm+Pcj0fDvAfLY1kxHg/K0/k4wi6f6ib5MW9pinEdoXwkK+WPxCOl27KwlMo1GiktV/cJ2pKI8jzr7+TNdZTluzbtVGfdqzSlKaZSUitSVMsfi8bCvF5JZah+SoG8vNxCsQLkp3KJFMoZhYgkmeJhV6/g+af/YaocBnaSt5NnFIWpPPCpunvoXvnJ7bxH2D3XuOTNugV18tuVW6uOEXet8lPOLNPhwckxkH+Ex0NsU34iD9uKNvL9yHPvRSRWyOfv34FgvVPdy8qtuC6ZnoPK2NW5b3IPy1ux7E0uJhfDgGFgb8SAEYbyGnqW7Wc3YaBiG6FCGy5EAcnCVqzHEyPa4/aXauLW5y7HW1NfwKrUNhQWF1HpTSEULUQoEmIiOQhT0Y2EUVAQopJF5TlJJTZFIsG82wt5LC6lPIJUsoDl5zPPrj9QUpJkWZBL0j777INGjRpBsguFVP6ury07z7YUJLdi5KxBOPWWozFhxQhEQlTQeTwZT1GpTyCZYFtCMeQXbHf1i0ZDSKaKqTgmEKZiGOY6EiuhcrzDLSoSoSLP+mkdDuUhUrgVRYVRJMNsY7HKLUBJIgSw7cmEXKqKqDhTXrEUwtyOlwAFlFFBgso0CU0sUsBrCimX7UiVUClnmwt5v/x4AddRJ+vCwkB5LSpSnWkxYZ5QiNex7qkQ6VxhPgpFjkhU4knWN0ySw3bGHXmgvEhOlKIJylX14vVqgywvflsETW1S0vEd1hgei7OdLonUlJJBR2ikWAcpSnK5IjkP49cPR49Rj2FV3lK2MY/1opwcaQyU7h0EqZLPkc9b5ChF4ojiEqyILsDrX/XAw/3vxYSNI4jSVYgXkbiF+Qyc0u7rVPnyhRmRhZAjjhGSwBATSQlJg7AgrChPSDIuyue7sRlLMR29Jz2BYfPe5nMnqeZ7EEtPZeRl53pI7irLW7yEaclbx33SeclfyT+jHc9j5/KU15LJwDBgGDAMGAa+CQaMMGQZQShfnWwmDOoxVo9wNMmXjn2n93avi4vvPwMPPF8fLZ+/B826NMQWKvt5ESq3zBuX0lpciO0l2xBKSulJoETEgApMlIpXiOVEiqMIpaj4FlFxTG1HYSKXyiN7nkuVzEw9wVKciouLnQJ11llnoXv37o4wSJmtzAuhtsRTMWxPbcKEhR/hqnsuxvTlnyIeFlkAwhFaSFK0liSp5lIBL0yFEC6RFWU7LRLswU6qJ5ntpJIdpqKvHv/0+0rZi7K3P5piviJaYdj+CK/JT1HpSxXy3ryWRCBGGYSoMIeKYiw7jlAJ70crTQEJhXqqQ4kC3ou91JRPqFgpHwVF6sFmfeL5lCOJmFO4lZ9l8j4h9txHmSdSxHOsu9qiehbqWSCX96B82bZwgvmcRSewYiSYN0YFtFWr1qhdu7aTbzgsIkJlnAqrkraFUck+vb2B9ULEQSkgOtqOsWc9Es4l6Yhja2gLGrStj9u7XIfabapi/toZ3wthiPKZR6mIF0SoqMc3oePrrXHNw1egda9GqHl/FYxd8AGKiNhiPpPvQhicVccRRFlPAtIR5zMOUkCSCknyQsUh9B/xFuq2uR43tq+JTv0f5mueQhExIguHT+nyK78t/GgRGV6wYIHb9s+ifF7bNyXAMGAYMAwYBr5vDBhhcH96s/cnuwkDlaQEFcKSEHtxF+PW7lehWsuzsQUrqA7lUqiMA0gVOaWWajCWbVmMCYvG4NM147CpZAPdlkgQCqj8JvKxvmA15m+ai0Xb59JpYwOmrZuEMXM/wNKChVSI853iGfRMV+yaol7v9evXY968eSgsLHTKq3pYfe/s7l4cKbMhKu1Lt8/D5FUjMWjK61i5bTHdRqjoh9l7TutFTu4iLNgyB0vDy7AktAhj54/AzI1TqNjn0x2LijcV9sDKkO5+E7iIiLjEqaRvCm/E9HXTsTK0mE44uViWuwKT507A0g0LECuOIDeyjeWFMG/dXIyaPhKfLp2EDcl17IvnP5KBgpICymk21iaXYU18GcbNGYP5myUzXkciEUlSVsW0yrBOa6I5LH8JNrFPfVl4MWbzvptjW0lGaC0gGVkVXolPFozEhPmjsS66nHfdQkKSSwLH5yrLA8lAXn6hU1Jff/11Rwx8L/eqVaswc+ZM9+KMHz8eH330kdv2vdrqfQ+SJwskSCQOcRKGFJOeS5jk66ul0/DZlnG4plUVLFw/6/shDK5HPo68xHasTCxDNZK/8UuD+nXr2wEtut/DutKqRctYknlde53C/03/wIgUytVOz1vPmUkElZazhEgLyyx0JI/vx8ZlfEKb0PjZu9HpnZbu3YiHSL5cflkaJPOKse2xKwHXrVsXf/zjH8usaf6cx7ny+EWEzj8Pn8/W3/QZW37DjGHAMGAYEAaMMPi/rlm6zmbCIB/84kgSU5ePx+1P1sTF7U/FJY+cjDt6V8fdT9fG9LVT2BMfw/LEInQc3Bx1u9bAlS3PwbXtq6Be1xswfvnH9CeP4Itln+CmNlfguseq4MZnLkeroQ1Q/ZGzUOOR83FL12scsQj83zO/tHp8LVq0wH777YcjjjgCzz77rHuilf3QSdFnPznqd7wJdZ6ohusfrYrxS0Ygwh7jBK0gCZKizq8+hNufuBI3PHMZ6jx9Jaq3OQ/1u/4HX66dgFxaJsKx7eyRlztVQA6COIeAMKg3WMuTrz2Gak0vRqf3muD5kR1Rv10dVG9wIe5sczMWrV2A/KJcdHvtCVx17+W4vhUJ2EMXou3brbAwsYT0IobpG2ehauOL8UDvm3DrY1eiasMLcE3rqnh/zgCSBNo7aHFYSaLwxEePokbbS1G7bQ3Ufa427njpJlz84FmYlzsL+SQdg6b3Q502/0GDNnVxc+ua3K6GCcveR27ReraDij0Jg5bzL66CY/92vHND8laEjRs34rLLLsNvfvMbXHjhhY5QqOf7jDPOcC5gESrMMVo8YrSMyGISo6XCkQfKJUWlGLRwyGUnn0pyIS0uE3I+Qq2HLyZhmPm9EAY98wixmUcLzMcrR+LeLvWxrXgtSmjNWbTuSzToUBPbCpaTuBSQMATWlICMZsZXxTiSyaqFdwAAIABJREFUgk9yQKKgJAtSmO2TBaeE7wXZMi06clMTOQoTXWE81K0BOr/bipKl61lY5EJkoTSxjIrvExyX8r9161Yn7549e7rno2OeFOjAmDFjcPzxx+OGG27A2rVry4jzrsq1c7uWu8nH5GMYMAwYBowwuD+62fyT3YQhgRR732cunoor7rwIl5EMXNHqbFzV4gLc1+k2LNw4my4+2/Hke+1wyUMno1rDs/DJ4vfx1FuP4BK6Ll1+7zlYF1qOTanleGX006jW+mxUbXMurn20Gh7oeTfqtK6NOzvWo51CQcS77n3Vy6ze7/z8fNSpUweNGzd2j7WyL7l6v6lm4o2PX8aDPevhrLtOwIiFQxg7QDcf9hQnGCsw/Kt+dJ25CFWa/wOdBrdFw171Ua3t6WjV+37eS/EHYboviWCw15ouVl6R01oWENVlU3IjPlk9BhfddSqub3YFlm9ZgFUFS7Fs6yJnSZG71sLtc/BV7gQswleYi09x8UNn4uXxvUlKolif2ophc4fijBuPZ/3eQU5qMfp99TLu6FIHK7cvx9aSjRiz8ANc1uhCjFw+DCtii9Hzk2fwj5v/hvGraUkoXomvVk7CmfVOxKD5r2NVySLkYAGeGdUBVe8/HeviS13cQoRWGi377HsA7rizgdv28SDCpKw4xx57LK699lp3burUqU6RzcnJoSJeBJorQH8n0Hk/SFtK1zpWQHU5WoKCEN2TGKMyKWc4XYYu+l4JgwLFKXW8Mq43Wjz9IIgMpOiitSG8ADc2vxiLVn5BAhEmgQkIw+4IaUU4SjAup1i8Ko9J7fNt3MZttTOf3IhxEhESpgJan4qYsUm3O9DZWRhIQhkfU0YWRBp2QxhUB2Hp8MMPR7NmzXgD2klKCYPWWkTaRN6UJk6caISBMqvo2dkxk4thwDBgGPhmGDALg/szm70/2UwY1EucCFNRpn5Ir3bc/Vw9XN2saqkwS+SBj02x1ahy/z9xzt1HY9GmqTxGP32mru+3wwV3nIDRU9+imr4VKyOLcdfzt6BmmysxOzSXpe1YCtnbHfiI7xrcIgzqBZcS27BhQ1dAZT8I6lVnHzHdhLZhyorROOWmv+LDRQPoarTFxQTEqKyH2Md/Y6sr0OKlW13Zcwpn4pI2J6J5r7u4T2sLiYX80hNpSpy/v3cZ2VC4EZ+t/AxXNDgfy/LmIMWgZLlD0aPdxUVsLtqEodMHkbQ0wBXNzsGFTU5B9dbnocfIrlR/gfWhXIyaPQatezRjGO1qjryzBRNWfoRrm16GJZvmsYar0eS5+ug9sjvV01zGV+RieWwJGrCXffycTyjptej1fhdc3+EyvPJZN/T/8jW8O6Mven/SDdUbnYG5Gz6nVSBC/366kzEIep999sVjjz3u2qu2SMYiP7KYyJKzYcMGd04/cpWZO3cuA40pjenAuEdXY0y7fIx9pAQftwM+bh/BkM6zULSZWWJUphnbEudIVJNz3se1ZYQhn65d8v8PRopy9yT5Kk4lnRuOl+eu17RoEJvC5JsTXsfDXZuQMOhedNMitm58+FIsWj0VRYxDKaKVQyNXaWQuH5fhn9Wu78HSI2w0ScGIZ5ZieKsNGNc6D6NbF2B4uzy82WoZ1k5lOxl6kM8A/zyOzCQ3vYe61S91SSKh+YYWBtVHxOCSSy7BBRdcgC1btuxEGHSuoKAAZ555Jh555BE3Uphc4fTMdtcWO7/rb4vJx+RjGDAM7O0YMMJQpu5k50a2E4Yke5OpkmBFKgf1nr8J1R6uwj0GD7O7dXtyE7al1uPcBqfgoodOw7SNk6iwrqciuwndJ3fE+fecgPcmvkY1fTtykstxU48bcOUj1ekapA5qBq0ypqCQPdAx+rpnIgxShqQUSYGVwqft66+/Hg888IB7oEHswM4ByBW99CIMDBt29f5k1Uc4+YY/Y9Si/mzJRiQ4oo7qEOb2tc0vQdMX65EeRDE/Nh2XtjkeLV8SYdBwqXRPoVKnAG4FC0uB072kgCqprrlU4D9dNgl3dr4ZSwtnc2SoApbP/BwhSoHJU9d/gTPr/wt9R/fB5AWfYOLiUajX5RY8N/w5R6JymX/U3NH476uPYCNlG+bISOMWj0Ctppdj8eZZ2FS8nErpHej+0ZN8Auudq9SS4vm4qdP1GDPvE7ZgLZ54sxXu6Xwteg7phN7vdMcL/XrgpXd74N0RL2BLYQ7rz25zPoRVK1Zhv333xwu9XnCyVBtEFtQubf/ud79zcSPCqJa//OUvmD17trt28fjNeLzBG+h4W190qtcfHeq+jQ63voE29boisoFsgYp0mCNm5UdFGD5EreYXYoFckhS47YKBg1GbwiSLBQX5mDFjBj79lEHopTKt6BkGx4K4Ao3KlceYkMlrpuCuzg2wtmQtaWoYM9Z/iTsevQFbo+v5PAILQ4ixDCHeR3XXfdSe3d8nxlGOyJRJGjre3wPt67+MDre/iUeY2t3+Bh6q3R3TxnA0Jo10lWRdaM0oJmoeevpudOjfjM0nKaIMYxE+e58qaWG4+eabccopp2DlypWunqqrT3oOS5Yscfva1nOqTFsyy9OUBJONYcAwYBgwDJhLkv6mZvWS3YQh8N3eFF+Ltz5/Fdd0qUq3pHPx7tzXMWnFx/Qb38Ae+s1o0vM+nHnnP/BA9zuxDHPw9tSXcFW7i/GvG/8PSxnovKl4FYbO6o//PHYFLnn4HLwzpy9GzB7GAN31DMLlUJVU7DL5mMtNRqQgfbnzzjvRtm3bskNSmKQ47eqFj7C7eCXdo/p/QQV3WGucXv9oPP5eU7z/1UtYuWWRIwhfrBuFGuz1v7VrTazkIJkjVg5Glbb/h7ueqo2tbEPc1TMI9tW9vBKnbd1fqZiq4vTcybip/ZVU3eeTkGymbYEhygxGlkL5+qjeuPWJa0le5N+SQg7jP65odDF6f9yDFgYO58pe6kmrxqHVS01JbjZzBKTtmLp1Mt3ALsWqxGISsjUY9tm7qHLHReg35Q3M2fwVmr1yH0nbvzBxyUSsTa3GiJlDcfU95zPWYQbvIZ8ajcATwVsDe7A3fIMjDIl4EsXJYhy434Ho+lRXnpdFQLEZgXuV9o866iitnFVHaxGG7dvliwMUbixB/ip65qwsRu6KorK0NSePw7pqHgrSSo7aJFehqXmjUav1+Zib9yXbyNgDBkWHad0o4nC1GvXpk0/G4uCDD3YWDR/QnvlZ8llr5KI478nnsSK6BlfeXwOjlo1grZJ49K32eOjZ+3lfjfREqwKtC1reGTQAxxx7DI488ki3n7l8/4eTijjbkIwUY/uGKLasimEr2xukYmxbyYBjiiJJeYVonaLkXLmNnr8dnYY04bZqwOB8tlNDE0cqQRY8ps477zycf/752Lx5cxnGREa1dOjQAQcddBBOPvlkNwCAf167w//u2+vbbWuTlWHAMGAY2BsxYBYG92c2e3+ymjDQBSfOuQBGffEOqtx1Ci57+AxUaX0q1//Ede2uxEz25oY5Nv0srm9oezVqtLoE1Vqdgxptzsal956PPh+9hgTH+P9s1Vhc0vBkXMnrq7U9DZe1/SeqPHAGJi0ZRcVPPc6aS4H+3lS8K0p6eoMGDXK+3fLd3nfffcv8uPfff3/k5ubu1p1FfjRt+zTDFQ+fh4tbn0ZXo3+gervTGGB8Mlr1etApdw+9XA/V256FC1ucgl6Tn8G9dE26tN2JzHMm+n7UC8kS1W8HMfGEwSttqudtrWqjKsu/uvkZuLL5qbii/T/w374P8O6at4AOQ5H5OK/ecbiqNc+3/jeqkkDV6ngJLrznn5g4/0NMXTcOV9x/Fi67/9945r2OdKBajSuanovzGp+Ku5+oj/XJtdjGkY5eHPgSbmhSG9cyIPrWx2qiboerMXnxGJKzTVhWuAptX2xGN6AqDO6+BLUePR//aXkebr3nauTmr3MjX6U4/4OWXx78S9xy8y1uW7KXwq6g5ypVqjgZS75aWrZs6fYVdD59Ov2RuEQ4z0SUwb87Jc45keKoV8lEDCu3LsAtnargmo7noOajZ7OdF6NOe5GlOOeUKFWiOWRt69YtXNkjRoxwVqTdKb9uxCLOZ5HP+uZyHonH3nocNVpcgv90PhvXtL2Uo1uN5h1IfDisr1zItLRs28bdo1OnTm6/IpztfCwYBUnD1AaT62n+Dc3HQSuXH2qVVotEJA/b45vR871n8J/2F7Gt5+K6R/kOND0V4+cPdWShkPEWBSKVGfCdfl9h6Ve/+hWaNm1aZgnxOFPFa9as6dqh92DSpElmXaiETNPla9sVf2NNLiYXw4BhwAiDUw+y9ye7CQOVYypF67ctxzsf9aF70bt4f/IADPz4TXw2ZwKVIA7RyfMRjtyTV7IZIz8fhleG9ETfD17EPLqfcBR/uhIVYFP+arw3rh+GjO+PoVPexYBP3sSYL4djS4FGedEQqZktDF551DCfPXr0QNeuXfH000+7eRieeuopt/ZuNLv64CXobD5rxUwMmTgIAye9g0GT38bgSW9jyCdvY/GaBeybTmDCjJEYMuEtDBjfFyu2L8GEWWMwePwb+GjCEKxYzSFYqZxo5ChNfqbZob0ip/uqd14Ty42e+CHem9APg9nG9yb1w3tT+mPKzHFIMno2wnkYNCfDis1L0HPAc+gzvDdWh5ZgRf5CvDHsFazesALbOCzroNH9MHB0f8xY9BUDagvx/tjBGDCqHz6d8Sm2RRm5QDcu2l2oEmve7Q3IwWxc3+4KTJg3kvaEAg7dmkePoyQmzRyNVwY9i9eHvYRJjG8o4rkYr3VzXtAaouXyKhfj2GOOLvPvV1vUrtGjRzO24TFIxlomTJjgtiX73G25tE5wwjm62ig5mZS63WgkIU3Ip8n68hhQPuyz9zB8yjt4j3IcMmkQPpg43A0vKxc0TTanEYb+8Mc/4Pe//z0WLVq0W0uR6ifFu5BxEAUso5AWqBDbNGhMf3Tr/zhJ1yfEXQoFlJPIXYIKvqxUN918k1O01VPvMbUrvATnOKcFh0ZN8ho3Z4UjtWqbklyONNcInz2f0eylMzB0/Lv46NOBeH/C2xhKDORsWkwLA13hmF913R1hkNwzjZLksaZn8fDDD7vRkoQ3f3z3bbE/hiYjw4BhwDBgGMiMASMM+gubxUs2E4bgxaLSRf/+ry30A09KIXOuQHQ9oXuIc24vzZgq0YReeVSsObQl53KoaNFoQwFZyEwY/Mut+IVMi8+zq7WUxBRnBdaiX5+0X5QqcX7mKFGvOyN6edbNIlzqu688HEaJ7ilUHOmm4mf5LX8/3cMvGsK12N2FR3izhFOsda0mRPO5GDxMhTNB1xktCfZca4hXv6g6GqmnbGHVIjyvoUoXbV6MwSRf7335Fp4e1hEX3fFvfLFkMsIkJFIipbiXlCR5aWBJYKw43X84jwSfhxRXzQ6dpPzzcjc6Rfq1115zt5FCrevTFz9krD8mshRjQG+CI//4FPdDh4pEUEYhuuAU8j5BawK5SrJa4oxH0XCnxRTE1rxgHojHHw8Cr3Xv8nItv68Rj0QYNAtzIpak25HaGSwMi3cKuuI0pNRHKb/PP//ctbF161au7EA+OyxF5csP9lkPEkORRDdRm5vwjrItnfgusDQpeFvkgfELnPsiWHYgS5PXxTRjN4mFYih2NVKTd7u75ZZbcNxxx7miVA/VtXwqvdFOxytuQ+Y/DJbfZGMYMAwYBgwD6RgwwuD/umbpOrsJg5QhOpA4pUm96tqW+1Cw1rZ80IOx6uW3HhCIuLMYUDElYYgwCDhGJVXXBEmTe6m3VcoWLRBU/IKAZ93rh395pSz7OQMCZU8KIRVDl9g77tpAZZoKr5LG30/ynHzyRRZ2RRhUfycrrt1szuxp171cT7criwHkJAVSdHVc6zy61IS5ljzClItmUHbl8J6xKN193KzSmlla20FZRVROR08ehdp31ULNu65A/WZ1MeKzj7CRE5nll8ZZBL3oag8tOKx3lGVFOOxohM9L946zHkmncOejY4f2qFWrlgt4luKqpOt3lTRcqEiCT9pXkG+c/vopuikVsB35ag+PqZc9rrkbeC7OcwkO1SvyJWJRwHiHgYMGuwBf3Xf3GAjwopGWChmHEWJ8dSzK6BCW5WacJpmR21CAKZKKQkaRbNmMd955G2vWrHGB6SJFlbuXx6OwK0uYEo9F2bNPIhKnTIWdgPQGZCJBnCdIDlKl2BFZUNsTar9k4Z6hL3fH2pNNuRrNmTPHxY3oWHmykGk/U7l2fIeMTRYmC8OAYcAwkBkDRhiylCj4amU3YZCCEyhxgRuOem2VdCxIXtnX0JVSrqVwBzPrKp8IRbrLkb9OSl/gWiLlNeh5zaxMfZ8vuL+v7hncVy8PFVnVncfKyFGpwqc2BWTCkwrllZKY+aXTOSn+Sl7JD8ql4i6F1pGkgDQUlpIH5QvyezmIMDBwlkqpS1TwRTwCQiOSwXmkI1s4EdxWbAtthoK6Czh5mIjKjrr5Z6H6KlhYvdxBT7cjBRzFKKGeePb2K3ZBrjuyJijtjjTsNL9AqXVBCq5GBBKpCrFMJUc6RARc0nnKj7EPGtJVcpQ85FYkJV4uNjvqLiwFQcdau7Y7zGlm6aCdIfa+hziKl8hU0L7A7UdB0d4CECepUJlxxlSoLn6uCVfX3TzDHXWRTD3u+dzdMwkIT4CF4Lxw75N7F/RMKQO1Pa72E0s7ytx5W/URGZDcleRm513tMpGE9OOZyrXjO8vZ5GHyMAwYBgwDFWPACIPXzLN0nd2EoWJQ7U0vmyMSIhPl0o8jA5EUb9nQdmDxUF08YXOKLEmCiEBwzBOO8s9Ox6XYVpQyXVO+jB37IkC+Pi62Q/tSwEUatM6Q3HU85+WZnq+8Eu/ct+jppnVAGAIrlawkmrk7XGrBCUjZLu5ZCTen9Hpkw7ZkUV4e2VAvq0NmnJlsTDaGAcPATxkDRhiylCj4ahlh2P0HZm9WnMqU8lKy4HqudyIM5QnArhT28nn9/s7XqOdaHz2vtFa0TicGznryAyjlsj6EnSuW6qM60p2KlhVZV0JphEFWKp92Rx5+yh9zq/vuvxUmI5ORYcAwYBj4dhgwwuA18yxdG2HYNbC9m4b/AHhl1u//UOsf6z67q//3RRi+PsqPJwtafwvCkGZBEKGQvL5vmcllTMTAxSaQJEQ4iZ3IgqwLcusK3L52kIXAvW3XeNqdvO28yc8wYBgwDBgG9kYMGGHIUqLgq2WEYdcfJj8Mpl/L117b3+Zl9gqt1ruzWhQUUDmlL3+m+6gMXw9frs8rH3Rt67zPVz6Pz7u79bclDKqD7qk2qK3JJOtCP/7KuCT5dvkyfFv8cV9nb3ko5hBM3t9e53SdJxHaT9/211ZmLTerJGdQLoxt4+Ro25k4yhNH3ArTwhJSu3SvtBQVafmW2KhMfSzPrt9Vk4/JxzBgGDAM/HQxYITBa+ZZujbCkPnlkqKpQFitNayq5mC477778OCDD+Krr75yx77Jx0kKtAjHunXrnIKb6Vopv7qnD5BVPl8HnVOdHnjgATdUpxTy8mRAddVxT260rzzl82W6f/rxnQlDEHi9I+haloHyKeZG2Bk8eDDuvvtuNwHYwIEDHfo9WYhqiE8mv1/ewuDbJMV/06ZNZc9gp3pRMfeykJxEsDxRkKyUlF9ljRo1yslq2rRp7lh6OZm3aUHgMLAFyY2YunYiPl7xASavm4DNnO+jMElCoiBmRxbkthTD9oJC5IU4UhGJkb935rIzY86uMdkYBgwDhgHDwN6IASMMWUoUfLWMMGT+MEnx8z3XUr41kdhDDz3klM9nn322VAkOrvdKonrBJVMp9dr2yr9efi3du3dHgwYNdrq2/IehV69eqF27NqpXr478/PwyRV/lSelXj/orr7yCf//7305JLn/9hg0b3ORaN9xwAxo2bOjutWuy4N2CNCoQZ4IIBYmzswGFpUnHGACcinA+CAZCB4HPmWQXx8CBg9CixcM49NDDcOKJJ7k6aESrgCxw9CoShjjdeko42UMxZ+NOl5W2tWj+gssvv9xte9KT3lbJefLkybjxxhtx5ZVXYu7cuV8jBCIMM2bMwAUXXIClS5eWO1/OFaqM/KhdlElRCPNWTcV1zavjkkZnouGLDbA0tgR5dEuKupGmNIRqHMtW5OCW227HrfXroWOlZ3LOJDs7nv6MbdvwYBgwDBgG9g4MGGFw6k72/hhh2PWLqF5r/7HyT/H//b//h+eee87t+p57rf2ybNkyp+hrX9frnIiDlrp16zrl1e2U/kip9fdQ3vPPP98pwGPHjnVWAn9Oa5WXvvhedZ9H1+fl5bmx9L0VQvmlhPs85ddxju+v8ftjnJ8Afu43zXKm+c5Ubc3d5ucDI4EocRPIZZKb3K3iKCmdJe3KK6/C6f86gwWAFhPOjUGiEA6LhQTLypXLsXHjBr/ryJCXpbcMlJ3khidmaoMWPYfDDz/czTysWYp1rfIoeeKhfCIcjrxRwZeSr/gEERaVE7h/MaA5xNmZOW+BAqodueFQsevzNmDWmi/xzMBOePjlB7A2nuOGa43xPl6O2zjz9KzZs/G344/H0UcfrduVnfN5bJ0JL3bcsGEYMAwYBgwDMRhhcOpD9v4YYaj8h8orq0cddRTSLQw6rkXWh1/84hfOAnHAAQe49bXXXuvOzZs3D+eddx5++ctf4pBDDsExxxyDv/71rzvNqqsPhhTeSy65xLkc6UKv/OqcyIGSJtdSUhnlPzK6Xse09OzZ0+XTtj9ePr/2NdGdXI9EEOZP3IrG1Xui3XWD8Ejtoeh0zTA8es1wtL76LfRoMcRZHJJhKttupCTdq6IkchJYCRxhOP3fqoKrV5hzLxQVpTBgwLs44ohfYf/998N+++3r6nnQQQchNzfXTaJWpUoV/PrXv3bHNfPw//zP/+A3v/lN2XwNao8WtVFy0OLbJqIgK8z69etZ/v6lsjoaCxfOD4gAyUIkwvk5OH9DMlJEiwln1ubka0Wc1C2pORrCcgnTXAt0dWIMw3ZswkvDn8HDL96PDck1Ltg5nTB4eZ977rk44YQTdqqLr5OtK/+emaxMVoYBw4BhYO/DgBEGpz5k748Rhsq/lJkIgz5sWv785z+jT58+ZQ9bLkF16tRx+yIMin/405/+BBEOudFcc801uO6669x5/3HcHWHwloqXX34Zv/3tb3eKc1AZnhio0MoSBndvKsvF1PHXTANefPBzvP3wEvRvkYMBzddicLN1ePuh+RjRYx5QQMWck6NFmUQKMia6LWm5svpVOOP0M912hAq6lPktW7agatWqzm3KneBPkyZNnPwkY82I3LhxY5xxxhlO2b/55ptx9dVXu2v85G7phEHEy7fbkzet5Ram5bPPPnOkZMGCuSQMdIciQUqR6DhrSh4zlE804sRDik0o/Bph2GiEoYyYeczauvLfEJOVycowYBgwDFSMASMMTmXJ3h8jDBUDt/wLLQVUvftSTOWSpFgELVLg5VKk5Z///CdOPvlk3H///WjevLmLeViwYIE7591jbr/9dlx66aXumP9R2Trv75nJwqDzcq3RovuLoCi2wrs0qW5+W3kqQxh07xAV6BAtBkkaSvJnAEteBNa+DGzmOq8XsP0F7vcGVgxmodvY5lgJCYMsC5kJg2Y41lKjxtWMtTjLbat+aqfqKPL0hz/8wcVztG7dGk8++SQmTZrkzimflg8//NARBrdT+uNlpLUWtdG7AansdBloW89swoQJOJAWn6ULF7rZtFMJ+kuxrUuHxDD7cWBGJ2DWo8DcjsAXjwEz3+R5kQZOzOYtDC9/8CxavdwIGxKrzcJA2ac/B9s2eRgGDAOGAcPAd8WAEYZSRSdbV0YYKveSe8IgpVSuMd4lySvAXo46rgBckQe5DSkwWYsnFbfccouLUdAxXaukl0yKrdYiIJkIgycWuvaZZ55xxEX5lTyZ+VaEgfMKFNJNJ8UO+Tmj83HdsU/g3lPfwAOnvI0mJ7+Fxie/g3r/1xNP3T0UJbkkDHGOwhRSfTMThkQiIDZySfrnP09TlV091V6RHqWhQ4e64O7TTz/dyerII4/ciTD079+/jDD4dsrVSCTJk4p0wqBjSv68rBG6bsyYMdiXz2LZosUIF/JYLKhbzwcH495/9EHDk1/H/UyN/vE6Gpz6PDre1t/VNxoJc5SkwCWp9/vd0OyF+xxh0PCp5pJUuffmu/4BsetNzoYBw4BhYO/AgBEGp3pk749XdJcvX+6ULXsxK34xpaxLEZWiK8VWiqoWHdcxye2Pf/wjtm/neP1UVLWoZ3vffffdKZD3zjvvdK42Ou8Jg1xw/LYU3kyEwSvEutZbGHR/ud74c/75KU9lLAzK7yYo46hABckUCkJ0awolmUqYOBwriUGwz+FlQxxFicOJRqLbWd9dWxgU+KxFFoYzzjjTbefl5TsFXsHJGv1Iw62K4EipnzlzpiMHixYtcvLUBQMGDCgjDGqf2rpy5cqyEaiUpyLCoOfhiZOuEWE48MADsXD+fAZ3k1TQNSpOC4niMBT4HGKwcyicj8JwiIlzLURZTxIoxVsUFkWwJbUOsjC0pIVhE7dDJHcq18taay0Ww1Dxu5MuJ9s2GRkGDAOGAcNARRgwwuBUiez9McKw+xdXCu3ixYtxxx13QP70shz84x//wPXXX+/29XRFJo7nKDk617RpU+diI2Jx9tlnu4cvBVaylovSoYce6hRm+eUrv0ZFkkLsFX8RBs31oEWKqZLOa6lXr56779///nd3reIkatWqhffff9+d94q1dipDGFR2JBpxE5EVhCOsA4dNpQUhGWcwsBItAn4/lSxChO1IJPw8BxUFPMc5fOky3HPPvS5+44gjjqSyfhBkWVHcggiVkuqstqs9nTgU6amnnsog6CNcO6XwS+YKWlaw88UXX4z69eu7/FL8tehjo6VHjx5fc0nysnr00UedBUOKvO5VvVo1/KdDd9+hAAAgAElEQVRmTfR4voe7NhFP8Llp/gbO3MwUJhEIc51IkpyIFHB82c+WTcQTfTug6dP34rb216Hr253x0afvc/CoHS5kvi5GGHb/LlX0R8KOmdwMA4YBw4BhwAiDU02y98cIw+5fUimwc+bMcUG6ik9o06aNGxFJcxxo6FItkqPckdTzrziF2267zeX3bjFyGZIVQcqshksV+ZCyPGjQINcbLlcbfTB1XoRBIy5pkeKsY7peS7NmzdCoUSN3Xr7/qo/iAUaMGOHyKa+3cDz//PNOUdZ1Ol6ZD3L5nvP0a3Z1Lj1fTk6OC2JWvVq2bOnSvffe6+IVtm3b5uTQr18/PP3007jrrrvcULMiWbpOxEpt9e2dzeFKNQGcZNq7d283kZuXo9olmR977LHadLJSPSQzLd26dSubaE+yUmC16tS3b193XnnVpvLJ3z9aEsLEhWPwyrCeeO3D3nh1eC+Xhk4aILpQJk/JVstZZ53FOSdOLCs7XSa2vUNeJguThWHAMGAYMAyUx4ARBqc+ZO+PEYbKv7SZnqJXMKX0py+SrZRJKaRSYqXoektDer50RVz5FRTtLQzaV/l6sXR9psWfV36f78UXX/zGhKH8C/xt9lWHTIvaIlmIhFW0SD5KkonWvi3KK3nqWp9HxzTJnScMKlOWHhEm1UH5My2+XeXJQvp+hMHg0SK6TIkeFFH+3IoVEy+cn0HzNPgyPEGRpUiWJy3+nK0r/36ZrExWhgHDgGFg78WAEYZMGkuWHDfCsOuXU4qnPmB+nf4xkzKrfSmwWksZ1jF/3F8nhVLXe2VZszdLMdUxkQxPCHx+Te4mFxolTcLmjyu/V6R1z/LX+Xya8VhzF+y33357jDCk10318oq4tpVU/2DCtKAd2lcen9evfXtFBCRXkQEvX71Cb731VpmsRo4c6QiF7q3rVL6/n2SXnvxxX68K15qvoTQpbqFQbkt034q4WZ534GbatGk47LDDXD3OPDOI1/Dl23qHnEwWJgvDgGHAMGAYyIQBIwxZQgwyVcMIw3d/eb2ymekl0Hl/TttSXNP3/bZfpz8rTxLSr/H5Mq3L9957QpMp/w953MumvAzS97/t/UUMyi/p5XrZ6ZgnEd/kXlGRQJ/iJD1Mfj+9HD/fg6/LnpR3er1s+7u/2yZDk6FhwDBgGPhxMGCEwWsRWbo2wvDdX4Rvo4x+kw9QuhL8Ta7L5rySWTbXz9dNpEGjSMkFKUg7yJ/PY+vv/g6ZDE2GhgHDgGFg78aAEYYsJQq+WkYYvvsL+kMSBt9L/nP7kP6QMvt+ZSWCIHKTnow0fL8y/u7voNXHZGgYMAwYBn7aGDDC4DXzLF0bYfhpv2D2gfwhnx9n4GbMQvkUd+TBSINh74fEnpVt+DIMGAb2LgwYYchSouCrZYRh73oh7QP8TZ+3iEFF6ZuWY/kNe4YBw4BhwDBgGMiEASMMXjPP0rURBnt5M728dtywYRgwDBgGDAOGAcPAj4EBIwxZShR8tYww2Ifgx/gQ2D0MZ4YBw4BhwDBgGDAMZMKAEQavmWfp2giDvbyZXl47btgwDBgGDAOGAcOAYeDHwIARhiwlCr5aRhjsQ/BjfAjsHoYzw4BhwDBgGDAMGAYyYcAIg9fMs3RthMFe3kwvrx03bBgGDAOGAcOAYcAw8GNgwAhDlhIFXy0jDPYh+DE+BHYPw5lhwDBgGDAMGAYMA5kwYITBa+ZZujbCYC9vppfXjhs2DAOGAcOAYcAwYBj4MTBghCFLiYKvlhEG+xD8GB8Cu4fhzDBgGDAMGAYMA4aBTBgwwuA18yxdG2GwlzfTy2vHDRuGAcOAYcAwYBgwDPwYGDDCkKVEwVfLCIN9CH6MD4Hdw3BmGDAMGAYMA4YBw0AmDBhh8Jp5lq6NMNjLm+nlteOGDcOAYcAwYBgwDBgGfgwMGGHIUqLgq2WEwT4EP8aHwO5hODMMGAYMA4YBw4BhIBMGjDB4zTxL10YY7OXN9PLaccOGYcAwYBgwDBgGDAM/BgaMMGQpUfDVMsJgH4If40Ng9zCcGQYMA4YBw4BhwDCQCQNGGLxmnqXrnxJhiEajyAS0H/N4PB7Pinqkt9nXKV1GiUQi6+qZXmfbtj8chgHDgGHAMGAYMAwIA0YYspQo+Gr9FAiDlGApv8lkEl4xtg/Mzh8YLxe/lnzSyYPJa2d5mTxMHoYBw4BhwDBgGMgeDBhh8Jp5lq5/CoRBREGLSIOWb6oIK79ScXFxxh53X6YU7nSl231MdH0sgsJYAVKIoQQJsCSEiwoRiVMxj8nyoTxBUj2/VgYV+EwfpqiUe6Z4WRnaj7jky424c0EZ8ejOZfn2ae0XPdfydfBtzFQPfzxTvkzH/XW23vm5mDxMHoYBw4BhwDBgGKgcBowweA0uS9fZThik9H722WfYd9998Ze//AX//Oc/nSQjESrUpUTAr5U3FAqVWSJ0PBwOI5VKuWOrVq1ySrSOS6lX3sLCQnesqKjIrdMfU7GOUTkvSiURjhfwVArvfPoKGjxdCy363IGVqQXIlWKfUHlREgreq6QovYiMJCH9A1LIMgqiIcQjYcQTcRTGIwjF80lG8nh9COFEGOFkDBHWORajpSVKQpJGGnx7dOM///nPOOmkk/Dqq6+6evj2qb2Sg/Lq3pKLT5KD5OnrJIKmfDommRYUFDhZSUYqR/l8Of4aW1fug2hyMjkZBgwDhgHDgGHg6xgwwrCT+ph9Oz8FwiCFdtOmTRg7diz2339/J0QprOnJEwi1R4qw9qXcyqogpVd5//CHP2DRokVlinT69cqj5dBDD8UBBxyAiy66CCtXrqRyTNIRKUQSEQyb9jZuafMfPD/sMbR5rSGua1Ydm4o20dIQQiIVR7IoiUWLF2GfffZxqVWrVpVSrEOyUsSLgTArEEpLhdzOB0rIVcgZWBelncmC/+hIyVebN2zYgMMPPxyNGjXixXBESfKTTHxerSUbtVlrJZ0XofCkwB/3a+VVSi/Dtr/+wTOZmEwMA4YBw4BhwDDwzTFghMGpbdn7k+2EQQqrV+al7P/iF79wwiyv7K9ZswYfffQR3n33XXz88ccYOnQoVq9e7XrG9eLKuvDb3/4W06dPx7p167B+/Xrk5+e7sqUse7cnkYUpU6a4exSTfERoOQizl18uSA/2qIuOr7Z05+Ztm4q6ba7F9C1TkFeUi5AIChXqZCJwn7rnnnvQsGHDShGGMElJnN5EhcvJD+ZyPYvcgSk6k0SBqZDHEhtLSUM0SaV9hzVAbZMsJCO1QfsiDCIrIhAiWSNGjHBWGrVTeXV88uTJGDhwIIYNG4ZZs2a54yJXM2bMwOjRo/Hhhx9i+fLl7rj2VY6Sl7t9DL/5x9BkZjIzDBgGDAOGAcNAxRgwwpC9XMHVLNsJg3+xVNl58+ZVaGFYsWIFjj/+eBxzzDGoVasW9ttvP9fDP3z4cOdyNGbMGPz+97/HQQcdhKOPPhonnHACjjrqKEcufA+67qNF137wwQduO05XpDxq8uFkGOtCOajb5Xos2DYL8RQJBi0OLXs+iI7vNuEWYxlicaTiDMqmq5CU91tvvRX333+/U7B9G3a1Bg0cvZoMRdPLX0azS/uhSZW30azKW2hxaV/cd+mzGNdvIc0FsjB8vZdfSry3IKg9IgxPPPGEs6Z4a8cjjzziyIQaVqdOHefide655+LMM890spKMtCifv0akS+Tif/7nf9yxE0880d3HE5RdtcfOVfxBNLmYXAwDhgHDgGHAMPB1DBhhcGpY9v78FAiDFFQtIgxS6LX4nm6tR40a5RTatWvXunPyuf/Xv/7lCIF63XNyclxvutyNXnnlFdd7LkuELBZ6aVWGFG0tipXwhCGWTCE/Tr//ojhyti/DTR2vwcLcuYilYoxmSOC/tDbc9/wNtD5IiadrjwgDFXoRBinl9913324Jg/ImYmQCdEUqpjWhZBIrMaE0TeR6PFD0GdcrmCgGERIFSGf62Ki8X//61+7+F198MWrWrInFixc7awpLwPvvv+9crubOpdmidOnRo4eT39SpU7Ft2zY0a9YMhxxyCBYuXOgIgiw2IhFffvmlIxCSV6b72/HMz8ZkY7IxDBgGDAOGAcNAxRgwwuC1sixd/9QIgxR6LemEYfbs2c5ioHMiFLImKOhXL6V6yP1aVoUlS5a4uAbv6qS18lREGOKJYirndAVKFWN17nLc1vFqzM+difwSBlcz4KDNS83xYK/bOWpSzAUix0gYoqWE4cYbb6w8YYgHgdKDm6zD81VWo/f5EaYQXjq/AC+ftQ3dqyzBgrfZaHKaZDROa0Zm0iDCoOBwKfhqr8iT2qbgZy2ysOjcYYcd5kiBiIGSjo0bN86RHRED7Q8ZMsTJ+Ze//CVatmzp5JYud/voVfzRM7mYXAwDhgHDgGHAMPDNMGCEwalp2fvzUyAMUui1zJ8/v8wlSYqxXkadk1KsuIPOnTu7YN/atWs7hbdx48ZOAVYblV9EQu5LUqB1TIsfajWdMMh/X0syWYRwKIhL2BpZj/pdrsGnOaNJFbbx30o07loPb455gXq8etw5etC3IAxqQ1wWBhKTgT0nolfLD9Gr6Wj0ajaK6xHo3XQkejw8BDPH5jjCkMnC4BV5tVOxGrfffjuqVq2K008/3cnINYg/f/rTn5zrVp8+ffDMM8+gS5cubv3iiy8ih5YYBUhr6dixI371q1+5+Ae5cikA3MvcPoLf7CNo8jJ5GQYMA4YBw4BhYNcYMMLg1K/s/cl2wiAl1Sv3UvZ90LOXqHz3R44c6fz2Fcjsl+uvv97554sIqAwtGnK0devWbltlSVnu1auX208nDAqe1lKUKnJBzBopSXMvdOrTAo261OWZAkxcPhg1GpyDtYVLEE4FMQyKY5CFQWVV1sIQfEA0ilNQR3fjCn9o7cjgCqTjaqPWWhTD0LZtW7d9xhlnoEaNGm4EJB144403HJmaM2eOO68fBTU3b94cCxYscORCIyXJHenII490o0bJuqBF5MwTk0x1sQ/irj+IJh+Tj2HAMGAYMAwYBr6OASMMTtXK3p9sJwx6qdQTLrcZudHIVUbDox588MGQ771iFDQKkI7LHelvf/sb/vd//9ft9+vXz1kfPGHo3bu3O64AabnZ6BpdKxlURBhSJAzxRIojJVEZT9GSEdqImxpWR/Met+GWh6ui57uPITexnnMmFLi4Au8q9G0Ig7NQyErBORaC7R0vUzQqRZ0jHJG4iLyUHyVJMvKk6rjjjnPt8kq+5mRQO5VEhFS3O++80+1LDt5F6ZxzznEjR4mAeVn4fEKvhly1D9yOZ2KyMFkYBgwDhgHDgGHg+8OAEYbs5QquZj8FwiAlVj74ejHVs61t9XZrWFQpt1oHcybEnGuShgkt/xKLNCivCIZcm7Zs2eLmHPD5vJKsOAhvYUhKSU6KLHAo0iRjIeJhbI9vxLBP38GM/9/edwBYVZ1bk+SlvZf3XmKaPs1viiVoosYWE02MXSMaK4ooKqJA1BgMNmyo2DVYAGkqKCpIEZAyTJ+hDoIwzAxMozNIGfr09v1r7X3PvXcuMzCDzAjM2rjvabudddYZv3X2t/deMcu2VW/AgmvFGFOwy9W3XwQDRENZqb/PyNd8TofKdRQ4HiOIkYHHwdd+3gMjBy5zy3vm/dHNiDFYwI540o2L06Ry8DPzE5fgOvMwHHfccda/f3+3z+sBVtruvz+QwlJYigPigDggDogD5SbB4MytA/fnQBcMEaPZrx/QkFsM09A45jW609C45X6QNngRg7JoGDM9j3mN2+ALPb/EP/HEE26dgpLSXVjFGeVUYiVkF1EHehuq4aBUVofFzqq4eBy+yKMMrsFQjmvbIF64tgG/2Hfr1i1cR9CGhrd+lqWgl6FhwUBREi0aIoIhuswAi+DeYq9Fn+c9EwueC/Jx7YrU1FQ3LSyxSEvjtE2YnSkkPqLL077+JycOiAPigDggDogD+4MDEgwHrlZwLTuYBENg2AZbCgKSNDiO3QbXm0JkfpGn2KArD9dQ4PiGzZuLYSjXQDTAoIZwqKjA138MbC51bkr44o7jCrgIVXFmJIoGrPS8pmitWwuic+fObgrTptTt11YIXJEa62FommBoWn31/7gRN/Y4MHDtCrprHX300XbSSScZ12pgID77Urby1MdaeAgPcUAcEAfEAXFgdw5IMDhz68D9ORgEQ9Bb0NCWL11D54NzTX0p+QWdbjtBTwNnT6qAOKBgYM9BeSV7Eejmg6lTsTZDOaK7jnlXq2BMl7FHA4u8laOcoAwKkKbVzx6GSCyFS1JpaaRHpRRjGEpLOYZhd3ekppW/+4sZm494URTQvYsuWxwUXlBQ4FbFJhYUFbF5dLx3XIWRMBIHxAFxQBwQB/bOAQmGA1cruJYFgoEGogi9d0ILI2EkDogD4oA4IA6IA+LA/uWABIMEg4QIekH0h0UYiAPigDggDogD4oA40DAHJBgkGGQsSzCIA+KAOCAOiAPigDggDjTKAQmGA1wwsHn0W6e/euCnTn9+RWEgDogD4oA4IA6IA+KAONAaHJBgOAgEAwf7rlq1ygmGYP7+1iCH6tAfIXFAHBAHxAFxQBwQB8SBZgqGOpjXjAqtiQDn4ueg58WLFxsXPVMUBuKAOCAOiAPigDggDogDrcWBsGCgDKiFGKhBrMX+7rKAZ6sRa3ARV3dPgGsKLYkAFT6n14xdz0DHfmEz4SAcxAFxQBwQB8QBcUAc2P8cCAsGGroUDD42ZPZSMEAsSDA0BI7OCQEhIASEgBAQAkJACAiBQxKBeoJhb3dYr+eBPQzqZdgbZLouBISAEBACQkAICAEhIAQOagTqCQYuEhasghu+KycM8FMX9DCE3JKcWpBiCOOkHSEgBISAEBACQkAICAEhcAgiEBYMgViooWjAjVIWVCJWIFYh0hnJiYY6XuGZev0NvKogBISAEBACQkAICAEhIASEwCGGQFgw8L7q0ItAOVCGuANxK+ImxC2IuxAVhIAQEAJCQAgIASEgBISAEGhbCEQJBu9exJ6EnYijZm2wf769yP4xssD+OWKp9Xk3wwZ9GGejx062CWM/tnFjR9vYsWPs47FjsVUUBuKAOCAOiAPigDggDogD4sChyIEowUCl5N2RtkM1DErdad3eWWO3vbfVbhtZbHcOWWq56HKgI5KCEBACQkAICAEhIASEgBAQAm0DgRjBQMkAdyQIhreiBMPtEAw93863JRv8mAYPjcYwtA2K6C6FgBAQAkJACAgBISAE2jICTRMM722xu98tsJzNfrizUxUYBs1l3vYkG3abcaktI617FwJCQAgIASEgBISAEBACByECTRYMf38nv55gqMNsSbWInFWpNjQdazDTUrAlHsG+tn7K2n3BIcAxml/7Uo7y7PszEHbCThwQB8QBcUAcEAfaKgeaJhicS1JeRDCgW6GpgiHayNX+viNAgpaXl5uWO9//y50LU2EqDogD4oA4IA6IA+JA4xxosmDoMTzPsgOXJAmGfbf89yFnVVWVrV692rKzsy0nJ8eysrLcPo8VhYE4IA6IA+KAOCAOiAPiQEtyoGmC4b1i6z5smS0tjoxhUA/DPlj+zcjCHgUGbnfs2GG5ubm2fft2t89jRWEgDogD4oA4IA6IA+KAONAaHGiWYOCgZ67+zEHPEgwEouVCtGCgUCgsLLSKigrnlkTXJEVhIA6IA+KAOCAOiAPigDjQGhxonmBAD4MEQ8uJhOiSowXDtm3bJBgkkiQSxQFxQBwQB8QBcUAc+Eo40CzBQJckCYZos77l9ykcJBj09aA1vh6oDvFMHBAHxAFxQBwQBxrigARDy9v8X7qGrVu3qodBXxS+ki8KDf3R0Dn9z0QcEAfEAXFAHGhbHJBg+NLmfMsXIMHQtl5K/RHW8xYHxAFxQBwQB8SBA4kDzRMMW6JdkrjKc41b67mhhdv8atD1jWk/748/x30fsQhIg/+C6/XLiD2KlBOkr0VpXIU6ON771pfJHFEhKMCdqncQlSh6l2ki614HOaK3vBqkiD4f7EeXFr2/J8EQzBl8IJFKbdEfOXFAHBAHxAFxQBwQBw4dDjRRMGyxHsNzbdnW0LSqzpqlmV/r/nGvKSHaWA6MZ4oOX0rwGxx74zrI01D5rDVSTrAfadXu14I09be+9VH3wN0guoqDg6g0DTXItcan4W9s/TUNnAvS7KnkxgQDxUJJSYmLmkHp0Hkp9QdWz1IcEAfEAXFAHBAHDiQOtLpgCAxkGs++j6Ia21BPhVXDyGbkFRr+3uhuzJhuyCgP8nj5UYkyKhBZZqS8SJpGyo+p0NcTCJFoIcBa2Nboc9xvvK7YtDUonOdiqsSZSGhMMJBItbW1xoXddu3a5VaBPpDIpbboj504IA6IA+KAOCAOiAMHPwdaUDDQDA4FWsM0jKMiDeVqnPaRTkSBSAh6GoJt4/0X3oSnGOC/kNHOOnDg6grOuW3IiMd1rokWxIixjpMM3CAGbWU7I+KG7fTXmIx53fVwGn/OtSWqDHccSl8vD/OFIjaNhsYEA4UC12fIy8uzRYsWGdPppTz4X0o9Qz1DcUAcEAfEAXFAHDiQONBCgoHmbxUizWMf1q2ptvS0VTZn9kabn7HDUlJXW0JSlhVvr3AJqmGl03gODOdgy4vR+7604JciA1/Zndjw56qhQObN3Ya61ttn89dbNS38qFBQUGY97hpiJxx/hw0ZPNsJA1++kwLhynLyzM744/3W4aoBLnfQ97GzxKxv30n2+9/3tAsv6mNXXPmCrVnnK6iC/KmmEkEoKNhhCfH57l7Lyv31aOHAM7FiIZTVJ476bUwwMMnll19uhx9+uLVr18569uzpFncrLS11WwoKuixVVla6Y7otcX/nzp1uWw2weMxVpAcNGuRWkmZ65g/igURWtUV/PMUBcUAcEAfEAXFAHGh9DrSgYKABzv4DLxrS0zPsmX6v2sMPvWlnnH6rPfv8cHvo0aesaNMXUbKCJnBzAsuugKDwPQw01ikQfvrTi6xHj5ds2LCJVo0kHAJdXcu2GETKPBv41sd2512v2MBB06JaiIu09RHLoWH6PDnWTj/nQTv/yjeZzV3idu5ny+ykU66wzOxNVoW67r77Xetya19eskoqAAT2cCQmzrbnn3/XTjnlFsvP3+nP4zdUhdV4WNx5n8vtNvjTmGCgcR+EO+64w3r16uWEQfRAaAqChgJfNi4lzpCUlOQEx/Lly8NJWQZFg17K1n8phbkwFwfEAXFAHBAHxIEDiQMtJBhod9IMplUMc70uYh2vXFltN3V6jgnCoQI27bBhk61Tp36WmVlh11zdy265+XGbMGGRS8Neg4YDy6VB7MvnbE0Mvz3pNktOWeH2q0JGPPsiIq0wGzgkwQYNneFyU9q4nD675ebV2D/+Ndx6/PMD69BxqCuHl2ogL8oqa6xw5WZ3jj9JyVutU+c+uBa0AmVFVXThRQ+it8Eb9jwdqoJZ7bOFG2zqtGVuf08/jQkGEolGPRd3o2C4//77wz0M7F1gTwJD586d7Wc/+5kdc8wxds4557i0zMPxDwsWLHC9C4cddpiNGTPG0tPTLSMjw+WlaDiQyKq26I+nOCAOiAPigDggDogDrc+BFhQMgQnszWSOCWAoXFFj13d82u1TBwRf2hcvWms33jTA/nLefTbxk4X25usz7ORTbrIdcOdxgoFiIBhYwNyuPJYd6cUIrPETTrrd4uKzmcq5/bgd/DBLqBnWf0CK9R+UZGU4R+cpfx5GNCz/Sy97zNLnbbS+z39iHf72Gq764Ic3+0lbK0Ki4Lob+tnf733RJQiPpGAXQyj8BYIhr9B/yedg6JB+sXGTCu0P5z5p5/ylvz33wmSXmrfYUNiTYKCbEcNtt93mehiiXyKep8vSz3/+c5s7d66LFAannnoqL7nwjW98w/Uu0KUpiEceeaRNmzbNCYro8rTf+i+oMBfm4oA4IA6IA+KAOPBVc6AVBAO/vVfh677vJihcUQHB4F14OG6hOrDisb36updscVbI4R+5evR82SbHrXSGbb2fII8z82Gc09LmOQRu2qOHYa+CYWCy9X8rPkYwmE2euNTuvHOEK+vxvnH2t7+94/ZZLiPvJghPP/eJXdYBbkChk35YNa5G9IL9GYIhN0owBL0PGZ8tt9u7PWnX3/CYxU2b54tkBQ2EfREMgZCg8X/hhRfawoULLSEhwVatWmVdu3Z1tbAHgSEzM9MoJKJdnHhePQz6A/VV/4FS/eKgOCAOiAPigDjw1XOgFQQDhQIFA7/js4ehDILhSbfPgcRBqIBOuOKqp2xHxC3f7uzez94fkxkk8RZ7YLk3tEVKnm5/0q0QDFkuX/BFnwdBFu6/BsHw2uDdBcNpp95oN9/8pr09YonddMsQu+iiQTb+E18W81ehyRQ5rw2Yaaf/obulzS1icSHHqLBycOf486eLGxAMXjtZObabsBieCxEoQicim6YKhvvuu8+5EHHcAo19xk2bNln79u3DvQfsRRg8eLBLR1HBNNOnT7fvfe97GGuRHx4QzfENekG/+hdUz0DPQBwQB8QBcUAcEAe+ag60gmCobwmvXF1r113/pLOGXd9DjbeeK+FZ0+Gqx2zztoih3O2ufvbxJ3mRE4HF39gWKXmpPV2SEuq7JAVjGAIXqAFDZtqA4em2E41gC5iP4fU3PrKnnnnP+r04wa7v9KJddOkL9vH4+e5ayM63F15JtQv/+qjNXlDqzvOH16ogG+h2FPQi8PyfLn4YPQy7uOvkEdFg5MiLAcMX2qNPp2GwdKR+nN4txAoGGvqMAXmYoVu3bvboo4+GZzfi2AYGjmuYMmWKm3qV4xMSExOdeOCsSAycKSkuLs6++93vOsHAMqMDjzX4WX+oAq5pKy6IA+KAOCAOiANtjwOtIBhgQMMa54Q+xVgpeuHn2+3qax7DdKpmO2HT0niug8Fchv2/XvmgLcN0pATqhGUAACAASURBVEG4/Y7nbPh7C/xhYyIh+nwo4wlwSZoRIxiC8QNVsOy3oB39XpxiL7+ZZGuLfSbXDpTFYRKc/Yihd5/37G/X+/EJ/ozZpKk5dvLpd8HQn2yT49fb+KkFdu3NvWxd8S7nrsQejWjB8OeL6gsGNpfh/dHpdvZ599i5Fz5qDz78hj/ZyG+sYGAyvqw1NTW2fv1652Z07bXXWvfu3THAusBWr17txh8wHXsUfvWrX9m8ed7tKTk52Z0bNWqUW/CN5cTHx7tz48aNsy+++MKuvvpq+4//+A+XJ+ip0B+HtvfHQc9cz1wcEAfEAXFAHBAHyIFWEAw0W83Gj0u3a6/7F6YgfdruuecN+O73sYsu6WrLl28zznj61sAPrfvdL9vNt/a2zcXlNur9FLv99mftplv72cRJKa6MRn9ohQeWOHZPpGCIX+qSBy5JwRxJffu+bjfe+KB16fqidbnzVbv+5r72zHODXdpgrDIFwxuDxliXbmjr/YPtqX7D3XX+PP7UMLun1yDk/bfdfMerdnPXV+zF18ZaCe6BvQyxguG8Cx+2/IJIDwPLoED6YmOlPfrkELur50u2bNlannazHbmdmJ9YwcAHx54BCoZf/vKXdtxxx9npp59uJ598sh111FH2m9/8xiZOnOhKOfvss+2ss85y57/zne848fD444+7axQD27b5Lh3OkHT00UfbD3/4QzvjjDPczEnBmg3RvRn6w6E/HOKAOCAOiAPigDggDrQtDnwJwcBv9jTDG1+JOcbubfSw2o18bvSyu1AXWPP1klEloG8gRjCcclJ3mzsHXRj+qtsyEddkaCxUhy7WBD5LMQkrq/Z8n64l+OHUrtE9DBdf0MeWF+6sV1pdMGVU1NmG788niBUMwdgDbvcUArekIE30MV/0Xbt2uTEM0ecpQoLAqVmZRn8U2tYfBT1vPW9xQBwQB8QBcUAciObAlxAMXA4tmGg0MDFbe0szPWTgcpctwmf+w39yjl155d+t9wPP+i/+OO//tXz73PoGaNKIdyfarbc8Yif/5iorLNj0pSqOFQzRD3Bv+xQVQWSPwZ7SB+n2lEbX9AdEHBAHxAFxQBwQB8SBtsWBg1wwsMuAjkBB8F0I5Zhyaev2LVZZXeH6QHiVesJpiiBpC2wpFhhZU2UlV0rehS/09QcR70u1X0Yw6IVuWy+0nreetzggDogD4oA4IA7sbw4c5IKhAfMb9rqz2XHJz4zEvgWa8Py3B5+kBoral1NeNKDuKNcmLyL2pTSfR4JBL/7+fvFVnjglDogD4oA4IA6IA03lwMEvGBrpNqA04ABkbv1oC8qHKoiGiI/+vpvwe8/JcQwUDXV1WJ4uelDD3rPulkKCQS90U19opRNXxAFxQBwQB8QBcWB/c+DgFww0r8OigfLAH/C3vmDw/QvhpMzXgoG9HL63gaIhVCs3+9AACQa9+Pv7xVd54pQ4IA6IA+KAOCAONJUDh4ZgCBv+vj+Bh7TLORmRt9G9Q9I+2Orhkpu748UC6oVYqCcYmlsQ0ksw6IVu6gutdOKKOCAOiAPigDggDuxvDhwigsHJA5jWkR6GfbDLD9gs27dvdwuycRYjrr/A6U4VhYE4IA6IA+KAOCAOiAPiQGtw4CAXDNFCIehdOPREA9dCWLJkiRUVFbmVnbkas6IwEAfEAXFAHBAHxAFxQBxoDQ4cooLh0BINdGnatGmT5eXlWX5+vuXm5ioKA3FAHBAHxAFxQBwQB8SBVuGABMMB64ikhgkBISAEhIAQEAJCQAgIga8eAQmGr/4ZqAVC4ABGoDWnCjiAYVDThIAQEAJCQAi0YQQOUcEgI6cNc1q3vq8I8LWpF3nAdUv0Pu0rpMonBISAEBACQuBQQKBVBENggxwKgB2U9xA8gGB7UN6EGt0qCAQccQuJUCxUInJMkIIQEAJCQAgIASHQVhFoFcFAcGmHKLQmAt7y2yPuYeOwNdu1f+uKvgXtx3QQAOrmYOKeTDgDREJdFWIFTrfO6uj7lxkqTQgIASEgBISAENhfCLSaYNhfDVY5TUOA61oHth/NvepQDBxMgmssjfv8hrw/YlDu/ixzT+3i/Sh+eQyIMZ9ZOLgHCWSdYOBVBSEgBISAEBACQqCtItBKgiEwI9sqzK1734Hht6PMbON2s7XbzFZhu3JHJK7Yaca4MrQNjr/sluW5evZzuQ21y9UVugft+2e5TziEeEGOrMP+FvCGEoFCTEEICAEhIASEgBAQAi0oGEJmq9sE34hbE/DWFCkN1dXQuda7f9a+vKjcFuZW2pyltZa+rM6S88oRKy0pt9qSllVb4rIqRG73R2RZKNtFv9/c8hPQjj3FSDt9u3kPyUurEHE/oW0yz7mI87i/2OjbF7Sz/jYZbY/ECuyHIsoOymedTYvIE8YjUk+kfDyLZaG4FPUsRd28h3D7g/vY05bp67c5Bc873O7wtQq0JbiXUD3AjLgF2CXl4HxOhc1Em7LW1BodkeCQ5IQDuaQgBISAEBACQkAItF0EWlAwhJwcnLUROI20lunBeoI6m/5wuUAaY/NDQ3U1dK75Je8tR0PtrcU90AVp6ZrtNienzNKyaywxp86m5ZYgllt8Lo6X+ZiALeMMGI/xzY41yFOLWIVYgTJpmFZiW2UJuRWIla7shGW1KJ9pG6+D9cehrAYj2hcHQ5ppEhCTcBwdE0PnuOV1H1E3jPCGYjzONxSj0yYiTRLuw0dfZ1D+nu5jb9cSKD5gmCctLUMsgXFfFjLwIdrCbQ/uYW9b4Bxzj2wv207xFlyrfy/174k4JuLZJOZAfOAZpqFNmWsqrRz8kWDY29un60JACAgBISAE2gYCLSIYaHJXG73oEXjAwZM1u7BDf4dVZusLzEq24PMljGp3nQkRAludRrvLjGyhXXepDjO2VKCMOpozNMh5FgnrQuKExzUlOIafSiX8KlwmJmEaHNQiVqEdq5aYLUo0K16OizStmT+0YVqWXbbBLDcD8XPkZRoEllFTCj+fQrPM2Wbz083yspEd7aqleRUuydfN8zXw82B5rJ4JsHU73DLgkgs8Ds6FTjVl05BgqMF9ssW5RWU2O78OX41rsK2xuSuqbN6KcvQ2bLdUCIdk9DQk5taix6HWCQh+3Y/HOR9h4ENY7DnWQRAYyqix1Pwqm1lQaTPz8ZW6sNpS8mG0hgRDYp4hHdNCnCBtAuqoF3Ge9cxAOxqKcblmM1BGIvKlFVTZnBW4n+W1xq/pSTSOYYQnQpRQmHgh5Hsg2CMR2xvAc/XqjmpLPHskgFN6YS3updrScU/pBbw3lIv2sexAYO37FvXDmE8FPv4+8JU/D4Y/RRbaFulFafo+75H5UvCsk9BOJ6aATQruYeaKOksHVokUcOg94DPhfcbjeSTi2aUgJuO+EnPKLRWCL33pTluyttLNjUQO1YXfs6awUWmEgBAQAkJACAiBQxGBFhQMIQOZVjIN/bodVpI61qY80NXG3XWjZTz/BIxuGOMM1UhUDWuZ2xruw4qugrlCA7oitGU5ODF18KtmRQVIA9HgDHla3DTImQAZKrda7tuvWMYb/S1l2HCcwjmWyYiQ8f5QG3rjBdbv9CNsW9z7uE5Dn3UwDXYr0VaGeZ/akA5n2IQuV/jj4BdiZ9w/b7a3Ol5icffdYaOuvsR2pCe4q7VsPwKrzE1Ls/jXX7bcEf0hkjb66+4ifpisBpVRnDAP75P3z20zAwVDLcuJChWVVe7rcPbaXc6g/gwabQysw56PvG7/enqQ5awrt9kFpZYGgzgwUml00miNh0E5I7cKEV/09xLjnZEOgzOvxqYs3GTvTc+04ZM+s/fismzsrFUwXtGbAYM+BY+Lxrw3slknex6io2+HFw0UDrHRbHpOrS3ZbDZh9kq7s8/r9tCrH9q8lRAQefhazy/2EBsJS1kPBQnLo3EPMYRtdPRGvxcXbH+8S8e0MNwhDiZkbLDhU5bgXpa4exkZt8TGpK+BMU4xQoy+nGhgL8xMCLe4JcXW8+nhdne/d4Bfic1bx7bTqGfbmxp9e5xIQu9EaiFEFdqXAvwWfmGoY4v1eGqoPT7oE8tYg/N5pcCizPc88HlkVVsedHvuVujnIrM0XEtfugM9DGVOMPB1cO/GvhAzio/aFQJCQAgIASEgBA5uBFpEMIQhoQFMWxaCYVv6NHvgvJNsVdIk25ydaYkvPW+vXvc3GNNrYTzD+A9CNQx29gQEgceVMOhD4cWOHWDMp+IolMaJBlcJqkE56GF48U8n26LhA23jogUuXVRptm7pIiteNNOmPtLdiqaORl0wiygaWA4tpCp4b5dusuQn7rEPrjvPZvS4IVSz36xfNMf63nYN2g0Lq3qnzX72QRv18H3+Yshur4Xxv2HdKts4P9WGX3OBlWcudtdDrcQ+7ydquspaHNPoj26oL3GvvzUQHtXV1fbvf//bTjnlFPvtb3/r8rCopRu2w/jcaU8OGGft2n0f8duIX7fLbuxp81fSFaYEBqb3taffO/3cvStRE7c0svH1PzGn1Lo88G9r952jfPzaT63dt35mgybOR/khAxUGLd1kEvmVG+fqR7ozUUBQsFCs1I/8ur8YHT6d73vZvvGjE3AP/+nu5UfH/8nmFJRbCtyukuBW4wVD0JvBHo2GBAPFQp37wu57M9i7gbZBKH2OOv7vdx2s3bePtnbfwD187YfW7ge/sN9d3NVyiiGM6E6ENvqxGXvb+h4JZ8zDiA+2qejdGZuy0Nodjvv45v/hPn5gP/z1WfbGRzNs9goa/HsrN/o6MY0IIueaBZzT8mpt8PgMO/Kk81H+txxe511zu02dvdzmLNsFUVBq6cAsbxPu9/g/20+OPc1uue8xS16y1WbmbLclq0ud4PSCwbN2r0RUAiEgBISAEBACQuCQRaDlBAMt1sDWWLHMXr/uEiubMw0GOdyFQpbxxMd724wH7oTx/YUNvKeH9bv4j3BVKrbytavtOQiDZ6+6yCxnIdLXWEVhnpVAdLx70xW2YcirVpo83dYkTIdbESy5oHeBj6l6lw267GzbmDwVB5XI6c0eXqqtYW8CGlWy3VKe7WNFn45F0Wio62XANdezsQs9Bp/a7Bcetoyn7rPEntcxqw90O6K4qcA91NDgr7Cq8e/Z0PtwD2VwlQrdbx01COut2WmjOl5s1cvgAsVATBjLkb9yoxVNGG75g54HJnBzYmDXRDNC4I60ceNGO/PMM+3aa6+1AQMGuBIoSbLW7bQkDHJ+/YOZ9uKQT23RylJLmL8cBuTXrOPdz9hCaB72LAQDg/34Axju/ELfhEhjNSHHLBUuNWd06G739h1kKVkb4Ae/xWZkbsA1CBb4xbsxBTk0mr04oTCpHykkfK9AQ70M8RAD+Fhuh514pd36wJv2+ZpqG5+61Nr9zzH2+Btj0dMAVxwY814whFyf2DbcW2QcQmDs+6/ykV4MumDRRafSMvGl/fjzbrUPk/Ns3vJSy/6izk679BY757pethjGtW9jE7AJ3UtDvRFpEAznXNHZTrusC9yBtlr8ko0w7M+186/rDhyjx0349sa2v/4x7g/YBDEFvSwzCwwCqtIuveUBa3fYsRi/st5Gx0OgfP3H9uLQCXg+W931ZIxZYM/TvU8Msks69bDv/fwkG5eyHIJhW4xg4PvTPF42g8JKKgSEgBAQAkJACBwECLSsYAgM5EVz7Zk/nmg1S2bBKMcYg1BYNvZdG3XNn3FUZcWz0u3NK8812wlfihLMA7oyx0be3cVKZtLwr7HChCk2tldXG3HtBZZwZ0cbd/9dNvieu+zz0R+HSuMGFVZutzcu+YOtTfGCoTpKMPiESFNebmnP9bWNUyexaGSjkIAAYG/Dro321pV/NCtcaMsG9rOEbujRYHD3AjPciRMeM+1WG9/xb5Yy6BWXxAkGigZGhtoSCIYLrTJ3kT9mXYz4KRo90IZdfLKNvuRU+/TJR/x11tHMQHekzZs3W/v27e3DDz90uasgfNiE7HWYGSe3zmbhC/rny+ts4fJKm5y2DF+2D8fX+hdt7koKhhp8OWf0xnXz3G7gBw83oDT4zv/hqn9Yp3v62YDRKfbWuNkwhnfA/x/iA+XGw/UlcSkM+ZxgTEGsMcwv5dFf/uvQyxCJ8ezFyDebmo17WY024wv54qI6+/6x59g1PfvaArjzJMJIprDwg44rnADwszbVFyeuJ4MCATHoyXCCAcfTUMYCCIMUuGql5JbZEuy3a/dTGzYtx2YCq+g8Qd7Gt7FuVf44LXeX/fzk8+wv1/S0hWuqbMHqKruxx+N27JkdLDGLg6A581ETI7D1z84/wxRgmAIMpi/cYUedeon16T/S5mPMysyl26xDlwfsW/93Isau7MRzAE4QevHZ1TZ/VZ0NHJuKnpRjbFzaCvQ8bMMsSWWuD8xR1e3tAzEdE/UjBISAEBACQkAIHAoItJxgCNCBe1HdvER79eLTYYRzzAK/zHsDZMfMJHv36j/huNxqVuTY6xADtms9jjFgGWH0o70gGCZiz5suPNe/Ewz47DncDQWURZceb9FDMGyz1y89C4JhCs5V4qN9KG/Y5oE4QJqEF/rY2unjkRemNQVDjR+7kD+0vxU80cOVvfzlvjbz9r/6elx+1oVDFgmxkPRYLxvRvRPys3eh1CrRQ4CSXKeFy4QB0u/fcCF6GEKCgWUwoozqVXk2/vnH7aOH/2mbsrNd8n35YS8DBcMJJ5xg77zzDu4XYxpCzcwq2mmJ+GqdkrXDFhSUWe9+Q+0Xp1xgv7+kE9xPii0NbjiBG4v/cs0v/XQNapqvfiIHMsPwnFlodn6nh2Bc/08oft/Ov7GXTVmw0X3hT4ARm4AZkDg42U81GhjxkS/qrrci7CoUEQsUDq4XhGMhIBqS0ebPMO3nS8MmuJ6SEdOz4YIDNx18MQ+PX8DYiUTEJLg/eVcr1sMYcn2COGAPSiAU/JgH5vdCJgW9ItnQrfc++TZck35lBegQIj5+QHLEvcgfR7sIRfbZFo6PiI2pcBF7+o1R9j9HtLerbuphXe/pY+3+80h7YdhkL0oayBNbRnDMOpIgxFwEdknAOAliIBXnz0APxv/+8hTLXLvd0rJW2uEn/B54fcvSc7chXTmeB8VeHXobquzVkRAMh/3GxkIwpLGHYU15lEsSyU7SKggBISAEhIAQEAJtFYGWFww0NjLn2mNn/8bqsmDow2XIfZ0H4is/HmFvXXU29mpsx9IFNqTTZV4w1MAARxj36L22Kw29APzK6Qz/KnvppsvNPk+G0U0jnWVBXNBFyH0JhSWOQc9vXPp7W+d6GGC+s9eAIWzz4FzlFkt88SErmv6xFwrOh4hKwOz5a/5qH3W+zJJ7322TbrvepnQ839LefMldc5Y+xzhUlNlnzzxiw25Ae/Pn4xrclNBzUoW66gkGDMweccNFVrPMj2FwbWA7aNFXYfakKvjZVKA3haEKKzPzfDNDtGAYMWKEyx2UkgnBkJAP4zl7O75k19h9GGB72DF/sG//+Hh7+Z04NwtQPA1tuvM4YxpjASAwIoKBX/3p2hMdI2KCvQKuh6HA7JnhSfbIa+Ns4Lh51vuV0TBOD7eH/v0xBt6WwnhnORw0zC/nMPwRKR44WxHHD7A+Lxg4CBkR6aMjv5yn4mt6KvKn5Oy0Mck5Tiyc1/GfcONhXpTD3gWWg9mAkpaVQlggYqyEm0XJCSDWQ3erUOR+OHqx4F2m0EYIhjw8liMxnuEvHR+wBXDdcnWE2sX2Bmsd+KljcT8UIeHyAgz9vXk8/T4FwwdTM9D+b1q7/zravokv++2+9mMb8FGyzV7JegJhEnomGKjs64iUFcxkxefinoHDFhhDMCSg12A2BNwrI5JQx3fsx8edYf91VHvs/zfity0paxPwp3CiEIMAw/PvPzIFPQwnQjAst1QKhrUVwdsEPgVsaiYxlVwICAEhIASEgBA4ZBBoMcFAMwMmMCIM8dWF1v/Gq6wiCb0F5TSQacTDt/2xnpbovubj635Rvo26Bb0HxStxDWb3jnz7qOf1Vjk7EccIIbehV2+60CxlDE5AJFShrNJibCEeGDkbE8TAm5eeaUVuDAOEBgWDb0yonwLt2bHeUp7rbRumfIByfM9CMHwgM2m65U7/xLbGjbPp93ez8bdcYWVLZiMdhAKnbK3F+IeHu9nYbtdCLHyG+8EMSKWYvqcGwoV1ed2B9AjVVTas06XoYQgJBn8WaVDWpixLebCzJXbC/awpDK40e0uXpC1btjiXJPYwMFRDeKAllrURs/FAMKSsgJtKDtxdlhu+MG+3I477vV152yP4Ug+DEcZ+HL44JxbA0MbMSVMyt2NqURquHDDMGC0WaOQHxrU3VrkOwwykYUzIw3iGlb7MP11zn7X/c2c3u9C0bMy8hOucPjQpC7MzZVe4GX2mIe9UzLDE8QT1RUn9Y4qSZKwjMRtiYNKsAmcIn97hHuThNKx19ilcnabBmOesTolY32BWHgZaZxXDqC/B9KVwvXHpeJ29ChQMwZoRvqfDG/poG6ZU5XXi9fqkOajnMJuSvcMSMD3pdJQ9Bfc3NQ9iBi5LdC1KxBiNGezNwPWp2SXYrwhHX08IL2IWisx39CmX2Flof1IWprjFvf/uglvs5PNusEQM1EjFs0hlbwoGJafnl0AAFMHAx7ODwAoGXQfjGChionGjYIrPhqiCeEoHZhNS19tDz79vrwyfZKdd1NH+eMWtmFJ3l7vOKVXdgGm4d702Ms6+/oNj7eO0AicYMld7weCkgvshqxSEgBAQAkJACAiBtopAiwmGsJXuTNdaWzMvyR64+Bz7YspHcCmabVOf7G1PXHUpjHcY/EwDIfHxw3fbMIxPsMVp9mmfe+25K/5i89/CoOAdm5DGWy6j8GX/3R43mxXMt7iXHrEnrjzfxg/u758fBzCjnMEXn2EbnGCowpdSfvMPQrWt/TzNVsZ9YB/+4yab1/8xWzftA6sqWoEELJ/uUgzoMVi9zCY+cLeNuvV6s7WwOkPlpAzpb0+ff7rFPXS3Zbz2rCX++1l74ubrUQac62NDdYWNvOHyyKDnqOuLJ71nz197ng25+gIb+wLucR8DZ0kqxsDvX//6184licWEZpC1TMx2k5xfZh+k5GKcwQ58wS61uYXb7FenX2jnX3+vzSqE4Ytbj0evQgZccLr862n70a/PsYs6PWgYs+wEA91fIl/IA7FA1x3OzlNrcVmcIhSGL8TIrJUw7GGsp+aX2nFnX2cX3PSAzYDhO3UJDHgY2nMhUHo+Ptjaff94u/3hQTYbkFEsBOLEudrgOHbth1QYwItR9qSkTBjx37JruvzD1uMRjUelIxPynehJyOXYBqybAIO434CPMSD6WLutd38MwIYowFd07z4E4z40QxOnFw0ipzplTIGgYQ/InFVmHXs9iy//P4EBvhO9GDCuYYDPgJHNts1aUW29nx9uPzjmbGt/QVdbBM0YlOW3rMe7P/kxE5x1Cm5AGBeRhjEE3z78ZPtblwctZ22NLcjfZX1f+9C+e9Rp9sncL2DMV6LNlfjKb3Zn7xfsyF+fYX++7r7QoGvfmxJ5HsQq0htDUcaelgSIhlkQYhmFlRjHUm3PDgQe7drZkI9nudmRUiDUAsGQHCUYxqTno/5ttniNBAPfIwUhIASEgBAQAkLAI9CCgoGf2iEE3LSn3hBfOTPBPn32IZvQ+w5LfP1F25UHKw92eh2+xDMUZ86zWUNftcTnH7F1cZOtcMp4mzPiNduQjS/5CBgNAbsdawi8O9SmYgzCvLf7W9bED/0Xe5/ACYahF59mWxMm4TwHb7LuUFuwNxV5Uoe+YIs/GGgL3+1vswY+Y5mJnzI3Wsu0aAt6K7LiJtqcdwdb3pj3bf7kce46fxZOGmPLRr9rmSOHWMY7g2zOyGG2NHEaOipKcZX1IFB70KkD065+cP3lVhvMkuQv+GTbNtiCT0ZZxtuDrGotrPV9DJxSlYKBg57DPQyh9SCyV5Vh8G6Jtfvpb+1P13Szm3r1tctv7+WMxz79R2N2IRjAME4TsJbB/KIaO6L975xB/tzA8fY5DFZ+gaZB79yGQl/IA7cdCgYa+sl4hO8nrrbfXtTdLrj5YbvziYH2u792QTk/slc/TEfZEBQwwlMKa20pvLDafRtTr37zR9YHRvLslXChQTnJMGAZG5ohifXPwqDqiZjBh1OQ0vDt0uMxu/7OR+ybR5xsZ19zr82DEEnAOg303Z+Fr/6HH3uWS/fMwAk2C+MY+MXeDyTmOgR+LQInHGDAJyJyrIObtcmJi3KbnLHJvvmzU+3vTw1Gz0Yp8tehfZyulZjAaM/eahd37O7qePSNSW6WppkQXWkQBano4UhxYsSLEAoHioV41BMPN6kU9DB0vvcFN+3sPQ+/Yj0gCtq1+4ldfttjrjeEg8/T0MuQDxFy3CnnuTr+/uRQy8DQnmDsQnjrelUouvyYjzg8D/amcKD76NQV9uzQyXbFbf/CDEmH2ynndbb4+cUQDOyBiBIMaKvrYcCMSmPS83CfW22RBMM+vo3KJgSEgBAQAkLg0ESghQUDDWhGGM/O9QcCgtOq7oA1FHIFqvIyAEZ2yNhm2uh1GZyR7cvAigPI56xxpEFZQaDocKfxU7nZhl56KlZhTvRXOcYBYxRc6eE6grqYxJcTckwKtSOq7FAdtXR3CosPnmSFrlIeoBTnfOX2/XgLllFuY274q1Ut4TgHBDayfjZ/zl1zKZr9wx4GDno+5phjbPjw4eH8vMOl8EVPwsq9j74x2o49G+sLYE2Bo8+41J4bNgXuLztgHOKrOgxMrmj8YWKW/eAXWBvgWz8yrPdmydlcK2EvgoGGPgTD5M922G2PDLefnXmtffP/nWm/Pr+jPTlkCnoXSm0afPI5uDgNqz9nYMaedl//kR11wh9s8XrM6AOh4gUDRYPvWaBAiI3JBWYfphXZNT362QU39Lazr7rPzrz64LxNLgAADTRJREFUbjulQzd7fkS8M+KT0I60PBj2mcXOyD7+rA42Ze4qrHLNFYz9YOboXgB+7Q8i14bgoOhk1J2Cex45o9COO/dGexbjPFKQNxliJAmCIR6CgQOj3572ObDEWg2YbWoGXLi4ajYXkKNQYOTYCd+z4N2f4qNclSi4pi3YYV17v2FH/uYSO+q3l6JnZwAGiMNVCB1ZFGIz4UY2PjnLfvrL03Av33WLqiVCNMXiQqEwHfftI/fpdoVBzyvMer3ysf3nr86xn+F53//ie/bpvA3ofYHgycQq01GCgbNBvTZiun2dgmGmBEP4BdKOEBACQkAICAEhEEag5QSDm32IZisNZ26DfXzBd8Y3RzhAP+CHVwI72vUi8AxPIFTjn/fIx4lIIlwJDpibaaqQi/tl9liHc+3ZW66zfph2taoc4w4YXHksA7F+he4ST/kQlBu7ZQqKBmx5yd0XBAzK4z+2gNGFKnxV/+Bte6JLR3vplhttc14wC1KkFpcuugqfs9m/gWA48cQT7e2330Zz/CxJlFZZmFY1nj7refS334JBsVvhrrINBjDO4Ut5Gl1tMEh27kq4CvUd6gztEdMWWHLWTnwJ51doLnDmewG8S493ieGsRRQTHMw8fQm/pDMtDH2IjBkYKxGHgcnx+NI+A0b4NFzjdj56LP7VD7MOYTB0vwETbB7cfhJg3MbB6KVooF9+Yy5JM1BGHNqZRP98rOqcAjeaePj1z0BMyYfogLvTdIxjoDE+df4G1PFtu6fvYAiUKt+74AxkzAqE6zTk/YxJ0VvkDYkfCiD2VrAngr0QPJ7BaWFhbMdxH/f85oQFDqtHXxuN62gTBl4nYexDdLkeL/bCRAYr+1mYOHgbvSEQEclLSyBEStwgZQzNwH0x4nksr7InUDYHLb88dCJ6WEKDxOFyFf0ciFs8nhEXouN4jqDngednAKcZ2bvQ9i1wR8MzysaMUZjRKhX3wTEOziUJ23SU/crbn9q3ftweggHuXVhDY1FoWlXH5hClm01MZRACQkAICAEhIAQOGQRaRjDQyOB4AooGmNEhC9tv3Ff+yBd8t25akCJknDgpwX3ESuQPHwfaA5f8F32WTSOe7kBcnTZSLk64QGcn1wxXNn7YJCYLle+O3T5+gnMNbnndl88iwqZ/aIeb6nAPBg5iQkWoxRwG7ioK6gin44nmh1rcXElJiV1++eV2xBFH2FlnneUKqcBvZlE53IF2YTAvvnzjqzVnQEphhLGaBsM3DQYwZ8mha9I/nnvPjji1A3oCYPhy5iIYrl4IBAu70a0nEmkcJ8LVJ70QogLbeBjjSTDcExET4D8fD7eaePRgxLHnIKfcMuF1dTUGWh97xtW2Aq5JyTRqEePQDs4C5FeA5raBCKM8Gen4hTwVayWkotckEWIhAQZ9PHsxIFSmoY65ECVPDJhsJ517iyUs2oQBxbhvuiNFCQbXk4A6eD4S/fSkcOFHu/iVn65HMLDRrmmLIUhoqAMTiht+wR80aYkddtwFNmrG0pBY8EIkaLuvg2skxERg5AY0w3hn+TMoGPBckjHOYyauzYLr00wY+hmF5fYkFqT771+cjbEI6CGhWxTuj5FjMlJDkdO/ulmnQvcSfj449ou5oWcHa2HEZbI3iTjUQXDVoAzgCUwwLtwOP/kK+9+jz7Tjz7zMPplTiLI3Y+xLSfgVCTRw85mpHEJACAgBISAEhMChgkDLCAai4wziKKs4vMudkNHMZDwMW+rcD4V66WPPMUeQgGXRkA/EAs77QnEuUo8rIcjCbUMh+nrsvksfU15UGbzir4YK5xSpod06N7VrJEVUti+9S8HAkJOTY6NHj7YJEya4Y6KxbE2ppS9Zj/gFfPsxneZi7GMlZm5TYcGnZ23GPgba4jgjf6vrkUhZjFl5MOI5FSsQ+4iVm5E/PRN5o2Ia9tNQNmMyBjyk4ph5WX4q0iejTJaTjJiCupKQJhtfrjNX7jKfd6OloA4ffZ7UJdzuHlNQXuLnKHvJZktluYvXofwiF1l2CvIw8tz8/G2Ws67SZmZ9EaqH5UXuJSg/DemDmJq5Efub0EaUhf1U7LOsFNxT8iKUk8V2BvV8YXPztlj+JgiYLOCI86nAIDam4b7TG4lpwHxmNspEHXwuabintEXrbSbqnsnngvML8Dxy11fbLJQ/E211kdeiYhr2WW/wHOq3gc8V5S/lveHZoT4+b8a0zE14XsV45iXWt/9H9uTLI23k2GSbu3itzV9SZHkrOJNZmL5uXz9CQAgIASEgBIRA20Wg5QQDMY01up0BzZ/AeI7dNpaHhTUSGqyDaaPrcRXjVGjbSFF7Px1UVj9lcLbB0t3J6BQNpqpfYDOO6IIUG0IawnaUm63bXGZrg1hcbmuKy2w1tqvdNrK/hte28Hz0NV4vQ55SW1tcsocYe700VI/P78v05fo6gvNN37J9vs1BG4Pt7mVE0u5+LXLfDV0L6uC1oHxuSxFLdotrtjRy3uEF3IFdw7HcPxPU4Z4Nty7Gpg9dDz+/+tf9s9y9Xbu3le3097tmcwU4UeXjpkrbjN6eYsxIvGlrnW3YVGGbt1RbGXjDELDWH+lXCAgBISAEhIAQaKsItBHBQGFC8yfYttLjDiyu6O1+rrohwcAqqkODwqtD6iFoQqxEa8qxz+vHajT1tynlHlxp6EzW9Bjg3dLbprUpItH3Rj/SJmhz8Hx4rCAEhIAQEAJCQAi0XQQkGFry2QeWV/R2P9fXmGAIdzyg7ppqDBsPxWoMGqlqZqzGwg4cXN30WAvB0vx6mtuu1ktfC8ywincTo8crgnmA/f7eeoyb0i6230fmqcXQn1rwITqybbyGZOFAtzYeSjCEIdGOEBACQkAICIE2iYAEQ0s+9mihEOy3ZH2xZX8Vdca2QccHDQJB7xFFQiAWJBgOmsenhgoBISAEhIAQaDEEJBhaDFoUHBjs0duWrG8vZQfN2EsyXW6TCJAdXBXFz0oWcEWCoU2SQTctBISAEBACQqAeAjGCAWYC/tuBz4uDUnfYHe+stlvf24JYbN2GLbPsLVyKLAg1SOoXRKNx0fQQmCINbZteStNSRtfBHMFx03Ifaql49wpCoGEEyA7fr+BnIPOpxJmG0dJZISAEhIAQEAJtCYEYwcDviWY7KRjStlvXd1dal/eL7RbErsOX2ZKtXBYtCPsqGIL82goBISAEhIAQEAJCQAgIASFwoCMQIxi4EFp9wUCxcPP7m+224UstE4KBS6T5IMEQIKGtEBACQkAICAEhIASEgBA4VBHYo2C4HT0MFAydIRi6DMuxxRIMhyoPdF9CQAgIASEgBISAEBACQqBBBJosGG4dttQWYQyD72Hw/s77NoahwXbopBAQAkJACAgBISAEhIAQEAIHIAIxgoGDHiMuSdE9DLeih4GCwY9hCCZe3JdBzwcgCmqSEBACQkAICAEhIASEgBAQAg0iECMYuG6s2TYMZRiSutm6v5NnXd9bh7jWug1ZaLk7GyxDJ4WAEBACQkAICAEhIASEgBA4RBGIEQw1mIUd06oijkxZYfcMSLG/D/nMeg6cZ73fSrMJyZk2e/4im58x2+bMn4P9uTYXcV7GPMvIyFAUBuKAOCAOiAPigDggDogD4sAhxoGwYGDPAmMFfkrgcbRyS53NzdtmcwvKLD17u2Us3WIr12y2oqL1tr5ota1dvwZxrYvritbhfJGiMBAHxAFxQBwQB8QBcUAcEAcOMQ7UEwwcwcAehmqIhhq/JAOOFISAEBACQkAICAEhIASEgBBoqwiEBUMAQB3EAnsa9hR92iBFkFNbISAEhIAQEAJCQAgIASEgBA41BHYTDGGlEHWn0dKA+9Eh9jj6mvaFgBAQAkJACAgBISAEhIAQOLgRqC8YAmXgVEBk6tQ93aIEw57Q0TUhIASEgBAQAkJACAgBIXBwI1BfMOx2L4GC2O2CTggBISAEhIAQEAJCQAgIASHQBhDYi2BoAwgcJLe4a9cuW7duna1du9Ztua8oDMQBcUAcEAfEAXFAHBAHWpoDEgwHgWAoLy+3rKws27BhgxUXF9vmzZvdlvuKwkAcEAfEAXFAHBAHxAFxoCU5IMFwEAgG9i4UFhZaVVWVVVRUGAWEojAQB8QBcUAcEAfEAXFAHGgNDkgwHKCCoY7z2yJwu23bNisoKHBiIVYwlJWVmaIwEAfEAXFAHBAHxAFxQBxoKQ5IMBzkgqE1VKXq0NcLcUAcEAfEAXFAHBAH2i4HDgHBwC/xnAJ2PyxN7T7q84drXmPLXXcO230J4fzcYfuaXlh0D8PWrVudSxJ7F2J7GPTytt2XV89ez14cEAfEAXFAHBAHWoMDB4lgCAzuhqx2GuJViNUNXWzeOWfPs7zyUHk40XQbf/e6mDdcJtsYEiK7p9ztjASD/gC0xh8A1SGeiQPigDggDogD4sDeOHCQCIYYe7qeEc8DGvlBjEnbrEOUUUejPogou15dzSoslDi2fWzn3guVYNDLu7eXV9fFEXFAHBAHxAFxQBxoDQ78f6BUENdHXjOPAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "4648acca",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbcd1b58",
   "metadata": {},
   "source": [
    "## 3.3 tuple"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42cee8f2",
   "metadata": {},
   "source": [
    "- similar to list (but read-only)\n",
    "- ordered, collections of items\n",
    "- indexable\n",
    "- immutable"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c39f26e",
   "metadata": {},
   "source": [
    "### creating empty tuple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6783a6e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "t = ()\n",
    "t = tuple()\n",
    "\n",
    "print(type(t))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e122be30",
   "metadata": {},
   "source": [
    "- heterogenours elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "c21ef057",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tuple'>\n"
     ]
    }
   ],
   "source": [
    "t = (1, \"Python\", 3.14, [1,2,3])\n",
    "print(type(t))  # <class 'tuple'>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4700ccde",
   "metadata": {},
   "source": [
    "- for one element"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "7be89b6e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tuple'>\n",
      "<class 'int'>\n"
     ]
    }
   ],
   "source": [
    "t_1 = (1,)\n",
    "print(type(t_1))  # <class 'tuple'>\n",
    "\n",
    "\n",
    "t_2 = (1)\n",
    "print(type(t_2))  # <class 'int'>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ff98fc8",
   "metadata": {},
   "source": [
    "### Access elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "41c6d44a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "5\n",
      "(1, 2, 3, 4, 5)\n",
      "(1, 2, 3)\n",
      "(3, 4)\n",
      "(3, 5)\n",
      "(5, 4, 3, 2, 1)\n"
     ]
    }
   ],
   "source": [
    "t = tuple(range(1, 6))\n",
    "\n",
    "print(t[0])\n",
    "print(t[-1])\n",
    "\n",
    "print(t[:])\n",
    "print(t[:-2])\n",
    "print(t[2:4])\n",
    "print(t[2:5:2])\n",
    "\n",
    "print(t[::-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5001d8a8",
   "metadata": {},
   "source": [
    "### Changing a tuple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9eaf8977",
   "metadata": {},
   "outputs": [],
   "source": [
    "t = (1, 2, 3)\n",
    "t[0] = 90  # TypeError: 'tuple' object does not support item assignment"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4a03934",
   "metadata": {},
   "source": [
    "### Why use tuple\n",
    "\n",
    "- read-only:tuple is immutable, e.g: weekdays"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff318021",
   "metadata": {},
   "source": [
    "### referance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "id": "a9762a37",
   "metadata": {},
   "outputs": [],
   "source": [
    "lan = [\"Python\", \"Java\", \"Go\"]\n",
    "\n",
    "t = (20, 30, lan, (1,2,3), 123.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "1bd9246c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(20, 30, ['Python', 'Java', 'Go'], (1, 2, 3), 123.5)\n",
      "Go 2309251473024\n",
      "(20, 30, ['Python', 'Java', 'Ruby'], (1, 2, 3), 123.5)\n",
      "Ruby 2309251473024\n"
     ]
    }
   ],
   "source": [
    "print(t)\n",
    "print(t[2][2], id(lan))\n",
    "\n",
    "\n",
    "t[2][2] = \"Ruby\"\n",
    "print(t)\n",
    "print(t[2][2], id(lan))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f584519c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7291eace",
   "metadata": {},
   "source": [
    "### Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "957b8680",
   "metadata": {},
   "source": [
    "- index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "id": "cb037621",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "t = (1, 2, 2, 3, 3)\n",
    "print(t.index(2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fff6d82",
   "metadata": {},
   "source": [
    "- count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "id": "a6aaaad7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n"
     ]
    }
   ],
   "source": [
    "t = (1, 2, 2, 3, 3, 3, 3)\n",
    "print(t.count(3))  # 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8487b712",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Membership"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "224ff3e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "t = (1, 2, 3, 4, 5)\n",
    "print(1 in t)\n",
    "print(0 in t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20897fda",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2521fbf8",
   "metadata": {},
   "source": [
    "### unpacking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "id": "edb80ad4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# before\n",
    "t = (1, 2, 3)\n",
    "a = t[0]\n",
    "b = t[1]\n",
    "c = t[2]\n",
    "print(a, b, c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "id": "f3c7e75e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3\n"
     ]
    }
   ],
   "source": [
    "# unpacking\n",
    "a, b, c = (1, 2, 3)\n",
    "print(a, b, c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2d39690",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1a44b4e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c0dfe15c",
   "metadata": {},
   "source": [
    "## 3.4 set"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "4a73e893",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64565419",
   "metadata": {},
   "source": [
    "- contains only unique elements\n",
    "- mutable\n",
    "- unordered\n",
    "- non-indexable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5a33f2a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'set'>\n"
     ]
    }
   ],
   "source": [
    "st = set()\n",
    "\n",
    "print(type(st))  # <class 'set'>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2ca4d633",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1, 2, 3}\n"
     ]
    }
   ],
   "source": [
    "st = set([1,1,2,2,3,3])\n",
    "print(st)  # {1, 2, 3}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db79388e",
   "metadata": {},
   "source": [
    "- add()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d88d570",
   "metadata": {},
   "outputs": [],
   "source": [
    "# add elements to set\n",
    "\n",
    "st.add(99)\n",
    "print(st)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a041e6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "- remove()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "af33196b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1, 2, 3}\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "0",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32mC:\\Users\\ADMINI~1\\AppData\\Local\\Temp/ipykernel_3244/420321858.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mst\u001b[0m\u001b[1;33m)\u001b[0m  \u001b[1;31m# {1, 2, 3}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0mst\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m  \u001b[1;31m# KeyError: 0\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      7\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mst\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 0"
     ]
    }
   ],
   "source": [
    "st = {1, 2, 3, 99}\n",
    "\n",
    "st.remove(99)\n",
    "print(st)  # {1, 2, 3}\n",
    "\n",
    "st.remove(0)  # KeyError: 0\n",
    "print(st)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a20475bb",
   "metadata": {},
   "source": [
    "- non-indexable\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ab4e00e",
   "metadata": {},
   "source": [
    "```python\n",
    "st = {1, 2, 3}\n",
    "print(st[1])  # TypeError: 'set' object is not subscriptable\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03516603",
   "metadata": {},
   "source": [
    "- update()\n",
    "\n",
    "add multiple elements into a set"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5375b09f",
   "metadata": {},
   "source": [
    "```python\n",
    "st = {1, 2, 3}\n",
    "st.update([88,99])\n",
    "print(st)  # {1, 2, 3, 99, 88}\n",
    "````"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "326ec19f",
   "metadata": {},
   "source": [
    "### Operations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a657490b",
   "metadata": {},
   "source": [
    "- union\n",
    "- intersection\n",
    "- difference\n",
    "- symmetric difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8ae31b0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "set_1 = {1, 3, 4, 5, 6}\n",
    "set_2 = {5, 6, 7, 8, 9}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "677a5edd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1, 3, 4, 5, 6, 7, 8, 9}\n",
      "{1, 3, 4, 5, 6, 7, 8, 9}\n"
     ]
    }
   ],
   "source": [
    "print(set_1.union(set_2))\n",
    "print(set_1 | set_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "99f844c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{5, 6}\n",
      "{5, 6}\n"
     ]
    }
   ],
   "source": [
    "print(set_1.intersection(set_2))\n",
    "print(set_1 & set_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0d34374b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1, 3, 4}\n",
      "{1, 3, 4}\n"
     ]
    }
   ],
   "source": [
    "print(set_1 - set_2)\n",
    "print(set_1.difference(set_2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "45aecb1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1, 3, 4, 7, 8, 9}\n",
      "{1, 3, 4, 7, 8, 9}\n"
     ]
    }
   ],
   "source": [
    "print(set_1.symmetric_difference(set_2))\n",
    "print((set_1 | set_2) - (set_1 & set_2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b749a97",
   "metadata": {},
   "source": [
    "## 3.5 dict"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e840dfe",
   "metadata": {},
   "source": [
    "- stores data in key-value pair\n",
    "- unordered\n",
    "- unindexable\n",
    "- access the values, with help of keys"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa1c394b",
   "metadata": {},
   "source": [
    "### Representation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e441a6a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "dic = {}\n",
    "dic = dict()\n",
    "\n",
    "print(type(dic))  # <class 'dict'>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "1751eea0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: 'abc', 2: 'xyz'}\n"
     ]
    }
   ],
   "source": [
    "dic = dict([(1, \"abc\"), (2, \"xyz\")])\n",
    "print(dic)  # {1: 'abc', 2: 'xyz'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "27f41c4c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'name': 'Clifford', 'age': 20, 'lan': 'Python'}\n",
      "<class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "user_info = {\n",
    "    \"name\": \"Clifford\",\n",
    "    \"age\": 20,\n",
    "    \"lan\": \"Python\"\n",
    "}\n",
    "print(user_info)  # {'name': 'Clifford', 'age': 20, 'lan': 'Python'}\n",
    "print(type(user_info))  # <class 'dict'>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1db01ca6",
   "metadata": {},
   "source": [
    "### Rules\n",
    "\n",
    "key rules: should be hashable,means mutable.\n",
    "\n",
    "values rules: None. anything can be stored in values.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b0815cf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "123"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hash(123)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6609a05f",
   "metadata": {},
   "source": [
    "### Accessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "6b636df9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clifford\n"
     ]
    }
   ],
   "source": [
    "print(user_info['name'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5349a888",
   "metadata": {},
   "source": [
    "- unknown key"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efa055f4",
   "metadata": {},
   "source": [
    "```python\n",
    "print(user_info['hobby'])  # KeyError: 'hobby'\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d4496b50",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clifford\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(user_info.get('name'))  # Clifford\n",
    "print(user_info.get('hobby'))  # None"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5619f60",
   "metadata": {},
   "source": [
    "### Add/Modify data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b263433f",
   "metadata": {},
   "source": [
    "modify value if key existed,otherwise add."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "b5225bda",
   "metadata": {},
   "outputs": [],
   "source": [
    "user_info['hobby'] = [\"Coding\", \"Game\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "47168ab3",
   "metadata": {},
   "outputs": [],
   "source": [
    "user_info['age'] = 30"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2278ef3d",
   "metadata": {},
   "source": [
    "### functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6ecac8e",
   "metadata": {},
   "source": [
    "- keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "104bfa4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['name', 'age', 'lan']"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(user_info.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d64a956c",
   "metadata": {},
   "source": [
    "- values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "47a42eb4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Clifford', 30, 'Python']"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(user_info.values())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "953af029",
   "metadata": {},
   "source": [
    "- items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "33ba7c1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('name', 'Clifford'), ('age', 30), ('lan', 'Python')]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(user_info.items())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "384a985d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name : Clifford\n",
      "age : 30\n",
      "lan : Python\n",
      "hobby : ['Coding', 'Game']\n"
     ]
    }
   ],
   "source": [
    "for k, v in user_info.items():\n",
    "    print(k, \":\", v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b873538",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "971e7681",
   "metadata": {},
   "source": [
    "### Deleting Elememnts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00b1e5d1",
   "metadata": {},
   "source": [
    "key should be existed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "04f73462",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Coding', 'Game']\n"
     ]
    }
   ],
   "source": [
    "data = user_info.pop('hobby')\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6b2cd76",
   "metadata": {},
   "outputs": [],
   "source": [
    "del user_info['age']\n",
    "print(user_info)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0739121",
   "metadata": {},
   "source": [
    "### Nested Dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "e00c1c8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "menu = {\n",
    "    'pizza': 10,\n",
    "    'burger': 30,\n",
    "    'fruits': {\n",
    "        'apple': 25,\n",
    "        'mango': 20,\n",
    "        'grapes': 22\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "e38ded1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'apple': 25, 'mango': 20, 'grapes': 22}\n",
      "25\n"
     ]
    }
   ],
   "source": [
    "print(menu['fruits'])\n",
    "print(menu['fruits']['apple'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "766e42e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'pizza': 10, 'burger': 30, 'fruits': {'apple': 25, 'mango': 20, 'grapes': 22}, 'juice': [20, 30, 40]}\n"
     ]
    }
   ],
   "source": [
    "menu['juice'] = [20, 30, 40]\n",
    "print(menu)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1eafee40",
   "metadata": {},
   "source": [
    "### Comprehension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "259ed249",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'a': 1, 'b': 2, 'c': 3}\n",
      "a : 1\n",
      "b : 2\n",
      "c : 3\n"
     ]
    }
   ],
   "source": [
    "d = {'a': 1, 'b': 2, 'c': 3}\n",
    "\n",
    "print(d)\n",
    "\n",
    "for k,v in d.items():\n",
    "    print(k, \":\", v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "b817cb65",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'b': 4, 'c': 9}\n"
     ]
    }
   ],
   "source": [
    "d_new = {k:v**2 for k,v in d.items() if v >= 2 }\n",
    "print(d_new)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "064bcea5",
   "metadata": {},
   "source": [
    "- practice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8677d2b5",
   "metadata": {},
   "source": [
    "using dict comprehension to reverse a dictionary, that is key becomes value and value becomes key.\n",
    "\n",
    "Input: {'a': 1, 'b': 2, 'c': 3}\n",
    "\n",
    "Output: {1: 'a', 2: 'b', 3: 'c'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d8da87e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: 'a', 2: 'b', 3: 'c'}\n"
     ]
    }
   ],
   "source": [
    "d_rev = {v:k for k,v in d.items()}\n",
    "print(d_rev)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b08a134",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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